Kopin & Goertek Reveal Smallest VR Headset w/ /2Kx2K Res @120 Hz

The Smallest VR Headset - about Half the Size and Weight of Traditional devices - offers Cinema-like Image Quality



Kopin and Goertek are unveiling its groundbreaking VR headset reference design codenamed Elf VR at AWE. The new design will eliminate the barriers that have long stood in the way of delivering an effective VR experience and overcomes limitations related to uncomfortably bulky and heavy headset designs, low resolution and sluggish framerates and the annoying screen door effect. The new Elf reference design features Kopin’s “LightningTM” OLED microdisplay panel offering an incredible 2048 x 2048 resolution in each eye - more than three-times the resolution of Oculus Rift or HTC Vive, and at an unbelievable pixel density of 2,940 pixels per inch, five-times more than standard displays.


In addition, the panel runs at 120 Hz refresh rate, 33% faster than what traditional HMDs offer - for reduced motion blur, latency and flicker. As a result, nausea and fatigue are eliminated. Because Kopin’s panel is OLED-based and has integrated driver circuits, it requires much less power, battery life can be extended, and heat output is substantially reduced.

FOR IMMEDIATE RELEASE

For more information contact:

KOPIN AND GOERTEK LAUNCH ERA OF SEAMLESS VIRTUAL REALITY WITH CUTTING-EDGE NEW REFERENCE DESIGN

The Smallest VR Headset - about Half the Size and Weight of Traditional devices - offers Film-like Images


SANTA CLARA, CA – June 1st, 2017 - Kopin Corporation (NASDAQ:KOPN) (“Kopin”) today kicked off the era of of Seamless Virtual Reality. On stage at Augmented World Expo, the Company showcased a groundbreaking reference design, codenamed Elf VR, for a new Head-Mounted Display created with its partner Goertek Inc. (“Goertek”), the world leader in VR headset manufacturing.

When brought to market, the new design will eliminate the barriers that have long stood in the way of delivering an effective VR experience. In fact, traditional attempts at VR headsets have been uncomfortably bulky and heavy, while low resolution and sluggish framerates caused screen door effect and nausea, making them usable for only tens of minutes at a time at best.

Kopin’s Lightning Display – A new approach to VR

To resolve these issues, Kopin’s engineers utilized its three decades of display experience to create “LightningTM” OLED microdisplay panel, putting an end to the dreaded screen-door effect, with 2048 x 2048 resolution in each eye, more than three times the resolution of Oculus Rift or HTC Vive, and at an unbelievable pixel density of 2,940 pixels per inch, five times more than standard displays.

Kopin first showcased its Lightning display at CES 2017, to overwhelming acclaim and a coveted CES Innovation Award. PC Magazine wrote that “the most advanced display I saw came from Kopin” and Anandtech said “Seeing is believing…I quite literally could not see anything resembling aliasing on the display even with a 10x loupe to try and look more closely.”

In addition, the panel runs at 120 Hz refresh rate, 33% faster than what traditional HMDs offer - for reduced motion blur, latency and flicker. As a result, nausea and fatigue are eliminated. Because Kopin’s panel is OLED-based and has integrated driver circuits, it requires much less power, battery life can be extended, and heat output is substantially reduced.

“It is now time for us to move beyond our conventional expectation of what virtual reality can be and strive for more,” explained Kopin founder and CEO John Fan. “Great progress has been made this year, although challenges remain. This reference design, created with our partner Goertek, is a significant achievement. It is much lighter and fully 40% smaller than standard solutions, so that it can be worn for long periods without discomfort. At the same time, our OLED microdisplay panel achieves such high resolution and frame rate that it deliver a VR experience that truly approaches reality for markets including gaming, pro applications or film.”

In addition to the game-changing new design, Kopin previously announced an alliance with BOE Technology Group Co. Ltd. (BOE) and Yunan OLiGHTEK Opto-Electronic Technology Co.,Ltd. for OLED display manufacturing. As part of that alliance, all parties will contribute up to $150 million to establish a high-volume, state of the art facility to manufacture OLED micro-displays to support the growing AR and VR markets. The new facility, which would be the world’s largest OLED-on-silicon manufacturing center, will be managed by BOE and is expected to be built in Kunming, Yunnan Province, China over the next two years. BOE is the world leader in display panels for mobile phone and tablets.

Technical specs:

• Elf VR is equipped with Kopin "Lightning" OLED microdisplay panels, which feature 2048 x 2048 resolution of each panel, to provide binocular 4K image resolution at 120Hz refresh rate. Combined with both 4K Ultra-High image resolution and 120Hz refresh-rate, Elf VR provides very smooth images with excellent quality, and effectively reduces the sense of vertigo.
• he Microdisplay panels are manufactured with advanced ultra-precise processing techniques. Its pixel density was increased by approximately 400% compared to the conventional TFT-LCD, OLED and AMOLED display, and the screen size can be reduced to approximately 1/5 at similar pixel resolution level.
• Elf VR also adopts an advanced optical solution with a compact Multi-Lens design, which enabled it to reduce the thickness of its optical module by around 60%, and to reduce the total weight of VR HMD by around 50% as well, which can significantly improve the user experiences for longtime wearing.
• The reference design supports two novel optics solutions – 70 degrees FOV for film-like beauty or 100 degrees FOV for deep immersion.

UploadVR implodes

What makes this shocking is this is a well funded startup to the tune of $5.75 Million, and they had a kink room with a bed and employees having sex.

They were written up in Forbes and part of the 30 under 30 best and brightest entrepreneurs.

https://www.crunchbase.com/organization/upload-vr#/entity

Total Equity Funding

^$5.75M in 2 Rounds from 15 Investors

Most Recent Funding

^$4.5M Series A on May 16, 2017

Headquarters:

San Francisco, California

Description:

Upload is dedicated to accelerating the success of the virtual reality industry through inspiring community experiences.

Founders:

Taylor Freeman, Will Mason

Categories:

Digital Entertainment, Media and Entertainment, Virtual Reality

Website:

http://upload.io

https://en.wikipedia.org/wiki/UploadVR

https://techcrunch.com/2017/05/15/uploadvr-sued-over-rampant-sexual-behavior-in-the-workplace-and-wrongful-termination/

Fwd: custom paper vr glasses

---------- Forwarded message ----------
From: Wendy
Subject: Re:custom paper vr glasses

Dear  Friends,

Nice day.

This is Wendy from Lionstar company in China.we are the profession manufacture of 3d glasses.

We know you are on the market of custom paper vr glasses..May be you want to get more information of suppliers.

 

As an ISO certificated and GMC, SGS, BV audited factory, we produce high quality products with 100% environmental friendly materials, modern production lines and strict QC rules.

 

Now we have cooperated with Disney, VolkWagens, KFC, McDonald's, SONY, LG, Skyworth and Lenovo…

 

if you are interested in them and need a electronic catalog or price ,pls kindly email us at lionstaroo8@lionstar-optic.com.

Best regards

Wendy

 

 

Wendy
Shenzhen Lionstar Technology Co.,ltd
Tel: 0086-755-84866026 Mobile/whatsapp: 0086-15277402946
Address: 5Floor,No.1 Factory, 4 Chuangye Road,Zhangbei,Xinlian community,Longgang District,518172,SZ,China   
Webiste:  www.lionstar-optic.com Email: sales008@lionstar-optic.com  Skype:2206915735@qq.com

Color consistently, why a picture with no red pixels can look red.

https://motherboard.vice.com/en_us/article/this-picture-has-no-red-pixelsso-why-do-the-strawberries-still-look-red

I think this actually solves the issues I was having with machine vision systems in uncontrolled lighting conditions.

Sent from my iPad

Smart Video Car Kit for Raspberry Pi with Android App - Robotic

https://www.sunfounder.com/rpi-car.html


Sent from my iPad

Piet is a language that interprets graphic files as source code.

This is “Hello World” in Piet:

It could also be written this way:

Piet is an esoteric language that interprets graphic files as source code. Each block of color is interpreted according to its hue, its brightness, and its size. There’s nothing missing in either of these examples; there’s no written code hiding behind the pictures. If you load either of these graphics into a Piet interpreter, you’ll get the console output “Hello World”.

https://www.quora.com/What-programming-language-has-a-cool-Hello-World-program
http://www.dangermouse.net/esoteric/piet.html
https://esolangs.org/wiki/Piet
http://www.majcher.com/code/piet/Piet-Interpreter.html
https://www.bertnase.de/npiet/

It runs a Stack based machine code similar to the Java JVM Virtual Machine so it should possible to compile real code in to these and run them.

Gradient-index (GRIN) optics

https://en.wikipedia.org/wiki/Gradient-index_optics

Gradient-index (GRIN) optics is the branch of optics covering optical effects produced by a gradual variation of the refractive index of a material. Such variations can be used to produce lenses with flat surfaces, or lenses that do not have the aberrations typical of traditional spherical lenses. Gradient-index lenses may have a refraction gradient that is spherical, axial, or radial.

History

In 1854, J C Maxwell suggested a lens whose refractive index distribution would allow for every region of space to be sharply imaged. Known as the Maxwell fisheye lens, it involves a spherical index function and would be expected to be spherical in shape as well (Maxwell, 1854). This lens, however, is impractical to make and has little usefulness since only points on the surface and within the lens are sharply imaged and extended objects suffer from extreme aberrations. In 1905, R W Wood used a dipping technique creating a gelatin cylinder with a refractive index gradient that varied symmetrically with the radial distance from the axis. Disk-shaped slices of the cylinder were later shown to have plane faces with radial index distribution. He showed that even though the faces of the lens were flat, they acted like converging and diverging lens depending on whether the index was a decreasing or increasing relative to the radial distance (Wood, 1905). In 1964, a posthumous book of R. K. Luneburg was published in which he described a lens that focuses incident parallel rays of light onto a point on the opposite surface of the lens (Luneburg, 1964). This also limits the applications of the lens because it is difficult to use it to focus visible light; however, it has some usefulness in microwave applications.

So long, 3DTV - we won't miss you - BBC News

http://www.bbc.com/news/technology-38778244?SThisFB


Sent from my iPad

I have shared an article from Hack-a-day on this earlier. 

http://videotechnology.blogspot.com/2016/03/retrotechtacular-eidophor-unknown.html

Then I ran across this great little article.

http://www.experimentaltvcenter.org/eidophor-television-system

THE EIDOPHOR TELEVISION SYSTEM

Authors:

Yanczer,Peter F.

Note: The information presented here is based on articles or papers by the following; E. Labin, S. M. P. T. E. Journal, April 1950; Earl I. Sponable, S.M.P.T.E. Journal, April 1953; E. Baumann, S. M. P. T. E. Journal, April 1953; Eidophor Training Manual and brochures, supplied by Bernhard Merk, Switzerland.
 

From the earliest days of television, large theater size screen images were a goal for most, if not all of the television pioneers. Some companies in the movie industry such as Twentieth Century Fox were also very interested at the time, because this might provide addition income from their theaters. So they actively promoted and supported the development of suitable systems that might accomplish large screen theater television.

The Eidophor system was an example of this and it was in use extensively from the early 50s, until well into the 80s. EIDOPHOR is a Greek word combination meaning "Image Bearer". Invented in 1939, the actual development work began in the early 40s in Zurich, Switzerland, under the direction of Professor Dr. Fritz Fisher. After considering the many problems, he soon came to the conclusion that a very powerful arc light source would be necessary to provide sufficient brightness on a theater size screen. The next problem was how he could efficiently modulate such an intense source of light.

Dr. Fisher reviewed all of the light modulators previously used, particularly the Kerr cell, as was used by Dr. Alexanderson in his large screen television work. He found the efficiency of this cell to be much too low for his purposes and so continued his search. Undoubtedly, Dr. Fisher would also have considered the Jeffree cell, used in the Scophony theater systems. Unlike the Kerr cell, which exhibits no memory characteristics whatsoever, the Jeffree cell was able to store as many as 200 to 300 picture elements, providing a significant increase in image brightness on the screen. But even this amount of improvement was not enough to satisfy Dr. Fisher's goal for
brightness.

Dr. Fisher went on to review some work done by Foucault on the optics of telescopes and also by Toepler who had described an optical system referred to as the "Toepler Schlieren" (in German, Schlieren means "streaks" or "striae").

His earliest design based on their work was similar to the drawing shown here on the right. This is a light control system based on the phase contrast principle and is a variation of the Schlieren optical arrangement.

The arc lamp at A, together with the condenser lens B, produces a uniform illumination of the plane C. A light-modulating or controlling medium is placed in this plane, between the bar-and-slit systems at F and G. A field lens is placed so that it images bar system F upon the opaque bars of system G. The image point at H is located in the image plane C of the objective lens D. This projection lens would therefore image the point H at point H' on the projection screen E.

But this cannot happen because the light beams are being completely blocked off by the bars of system G. It should be noted that the incident illumination of every image point at H, is blocked by the strips of the bar system G. However, if a control medium of some sort, is located at the image plane C and could be deformed in a suitable way, diffraction of the light beams would occur. Those diffracted parts of the beams could pass through the slits in system G and on to the projection screen as image forming light.

The next drawing here on the right,

shows a control medium, consisting of a liquid oil film of approximately 0.02mm thickness at the image plane C. For the sake of this illustration, consider this oil film as being supported on a thin, flat glass plate.

This layer of liquid is called the Eidophor liquid. It takes the place of an emulsion on the usual motion picture film in the film gate, as one would find in the usual projector. If the layer of Eidophor oil is of uniform thickness and homogeneous, light passing through the oil film will not be diffracted anywhere in the image plane C and all of the light passing will be blocked by the bars of G. No light can reach the screen.

The next step is to create a form of optical inhomogeneity in the oil film, point by point, that will diffract the light beam past the bars and through the slits of system G. This is done with a beam of electrons from an electron gun, scanning an approximate 3 by 4 inch raster directly on the the oil layer. The electron gun operating at a 15 kilovolt level, deposits electric charges point by point, corresponding to the scanned picture. These charges cause minute wave-shaped corrugations in the surface of the oil layer. Where the oil surface is corrugated as at H1 on the surface C in the drawing, those light rays passing through this point are diffracted and no longer blocked at G, instead passing through the slits and on to the screen. The more the Eidophor surface is distorted, the more intense is the light reaching the screen. A brightness range of 1:300 has been obtained.

The drawing to the right

shows the relationship between the brightness A, along a line of the image and the amount of the wave-shaped deformation B, in the surface of the Eidophor liquid. The amount of deformation on the Eidophor surface is proportional to the desired brightness level for a corresponding point on the screen.

The Eidophor principle of modulation is for the cathode beam to scan the Eidophor surface, controlled by a video signal in such a way that the resulting deformations are proportional to the instantaneous values of the controlling signal. The actual controlling element is the spot size of the electron beam. The smaller the spot size is, the deeper the deformation of the Eidophor will be, causing more diffraction of light to take place, in turn producing a brighter spot on the screen.

The wave-shaped deformations are caused by electrostatic forces in the oil film, due to the electrical charges placed on the Eidophor surface by the scanning electron gun. The wavelength of these deformations is constant, but their height is proportional to the level of the video signal. As the illumination of the image points on the screen are always proportional to the height of the waves at the corresponding point on the Eidophor, the distribution of light over the projection screen corresponds to the video signal and thus to the object being reproduced.

The deformation commences at the moment that the electron beam scans a particular point of the image. By a suitable choice of the conductivity and viscosity of the Ediphor oil, the deformation can be preserved for a considerable part of the image scanning period, so that it disappears shortly before the next scan of that point. In the ideal case, the deformation of the oil should remain for the duration of one picture period, but then decay as quickly as possible. In practice, 70% of the ideal is achieved. Since the screen illumination is maintained for this
part of the scanning period, a substantial increase in screen brightness occurs due to this light storage effect.

After considerable testing, the results were encouraging. A simplified compact prototype model was developed. This is illustrated in the figure below .

Notice that it uses only one bar and slit assembly, which is reflective and actually does double duty.

Another change in this prototype was the addition of a color wheel, developed especially for the Eidophor system by the Columbia Broadcasting System, using its field sequential color knowledge and techniques. But before this unit could be completed, Dr. Fisher had died and his work was carried on by his associates, directed by Professor Baumann and Dr. Thiemann.

Since there is an electron gun in this system, it might be well to point out that the electron gun and the Eidophor oil can only operate in a vacuum. The Ediphor oil characteristics are subject to change with temperature, so the system includes a means to stabilize the temperature of the spherical mirror and Eidophor oil in contact with it. This is accomplished with a small external refrigeration system.

Another view of the Eidophor Projector is given here.

It shows a side view of the vacuum chamber containing the lens systems, electron gun, spherical mirror and the Eidophor oil surface on the spherical mirror. The mirror rotates at about one revolution per hour to prevent a gradual build up of charge that would otherwise change the characteristics of the Eidophor oil film.This drawing shows an arc lamp, but later it was found that certain xenon lamps could also be used effectively.

The drawing on the right

shows the approximate size of the Eidophor projector. The space requirements are similar to those of a standard 35 mm movie film projector, as found in most projection booths in theaters around the world. Not shown in this drawing are the various
power supplies and the vacuum pump that are normally contained in the same cabinet as the Ediophor projector. Also not shown here are the cabinets that house the various signal associated electronic circuits. The over-all dimensions of this machine were approximately 5 feet high; 5.5
feet long and 2.5 feet in width. The weight of this assembly was 1800 pounds.

This photo to the left

shows a complete system, including the two upright cabinets (6), containing the low level electronic circuits and their power supplies.

In the main assembly, the projection arc lamp (5) is located at the top left and the vacuum pump and auxiliary services equipment (4) are directly below it. The color wheel (3) is located at the top center. The Eidophor projector (1) is at the lower and center left. The projection light beam hood (2) is at the top right.

In later models like the one pictured below,

the arc light was abandoned
in favor of hi-intensity Xenon lamps rated at either 3000 or 5000 watts. A color dot sequential system was also incorporated, replacing the CBS field sequential method and the purchaser was then given the choice of using the NTSC, PAL, SECAM or HDTV color systems.

The over-all specifications of the more recent models of the Ediophor systems were most impressive. They included these:

Screen sizes up to approximately 40 by 50 feet; 80 times brighter than than the best three tube CRT systems; up to 1250 lines horizontal, 120 Hz vertical; Video bandwidth, 50 Mhz; all digital control; white field brightness levels of over 10,000 lumens; projection throws of over 650
feet.

What a fantastic system! An engineering marvel, if there ever was one!! Fabulous!!! (Editor's comment)

In spite of it though, the Eidophor is becoming obsolete. It looks as if it will undoubtedly be replaced by the LCD and/or the DLP device, manufactured by Texas Instruments, basically an integrated circuit with teeny, tiny little movable mirrors, (pardon the scientific terms).

Peter F. Yanczer

Scophony was a sophisticated mechanical television system

Scophony was a sophisticated mechanical television system developed in Britain by Scophony Limited, which used mirrors mounted on high-speed rotating drums to project an image upon a screen.

The company Scophony Limited was established by entrepreneur Solomon Sagall in the early 1930s to exploit the patents of inventor George William Walton. In 1932, Ferranti invested £3,500 in the company, however in 1934 Ferranti turned down the option to invest a further £10,000 to re-structure Scophony Limited, and in 1935 EKCO replaced Ferranti as the company's main investor.

In 1938, the Scophony company demonstrated three types of 405 line mechanical television receivers at the Radiolympia exhibition in London: a home receiver, with a picture area of approximately 24" x 22" and two systems intended for theater operation, one producing a 6 ft x 5 ft image and the other a 9 ft x 12 ft image.

Several of the theater systems were installed and operated successfully but none of the receivers were sold as production was halted due to the impending war.

Scophony's system used several innovative devices:

• A split focus optical system invented by Walton, developed specially for use with mirror scanning systems. Light beams were focused by crossed cylindrical lenses, concentrating the light in two planes. This allowed the use of smaller lenses and mirrors, thus reducing size and cost. This was particularly important to Scophony since they intended to produce extremely large images.
• A light modulator developed by J.H. Jeffree in 1934 and known as the Jeffree cell, a cell filled with a transparent fluid which used mechanical oscillations to modulate the light beam passing through it. It was a substantial improvement over the previous Kerr cell, 200 times as much modulated light being available at the screen.
• High speed synchronous motors which could be relied on for 1000 hours of use, some lasting longer without noticeable wear. The Scophony system used two: a low speed scanner which operated at 240 RPM and a high speed scanner which ran at 30,375 RPM for 405 line transmissions or 39,690 RPM for the American 441 line system.

From 

https://en.wikipedia.org/wiki/Scophony


Scophony system at TV History website
Scophony system at Early Television website


Some real gems in here.

UK Vintage Radio Repair and Restoration Discussion Forum > Specific Vintage Equipment > Vintage Television and Video

Who has information about the Scophony? This talks about the Scophony and Jeffree Cell

LIGHT MODULATION VIA ULTRASOUND
Wikipedia: Jeffree Cell

Screens that correct your vision, glasses not required: Gordon Wetzstein...

Tensor Displays - Biggest breakthrough since color.

Nanotube Field Emitters Beat OLEDs

woaaah

http://www.eetimes.com/document.asp?doc_id=1324304

crts may make a comeback

Massive DDoS attacks coming from IoT cameras

https://blog.cloudflare.com/say-cheese-a-snapshot-of-the-massive-ddos-attacks-coming-from-iot-cameras/

33C3: Chris Gerlinsky Cracks Pay TV | Hackaday

http://hackaday.com/2016/12/27/33c3-chris-gerlinsky-cracks-pay-tv/

Fwd: BitTorrent Live’s “cable-killer” P2P video app finally hits iOS | TechCrunch

---------- Forwarded message ----------
From: J M

https://techcrunch.com/2016/12/21/how-bittorrent-live-works/?ncid=rss

The OpenMV project - OpenMV Cam M7

https://openmv.io/

The OpenMV Cam M7 is powered by the 216 MHz ARM Cortex M7 processor which can execute up to 2 instructions per clock

512KB of RAM enabling 640x480 grayscale images / video (up to 320x240 for RGB565 still)

MicroPython has 64KB more heap space (~100KB total) with the OpenMV Cam M7 so you can do more in MicroPython now

$65 retail ($55 to pre-order)

The OpenMV project is about creating low-cost, extensible, Python powered, machine vision modules and aims at becoming the “Arduino of Machine Vision“. Our goal is to bring machine vision algorithms closer to makers and hobbyists. We’ve done the difficult and time-consuming algorithm work for you leaving more time for your creativity!

The OpenMV Cam is like an super powerful Arduino with a camera on board that you program in Python. We make it easy to run machine visions algorithms on what the OpenMV Cam sees so you can track colors, detect faces, and more in seconds and then control I/O pins in the real-world.

Fwd: live "gov" webcams on oahu

---------- Forwarded message ----------
From: WW
Date: Mon, Dec 12, 2016 at 9:10 AM
Subject: live "gov" webcams on oahu
To: John Sokol 

http://www.honolulu.gov/cameras.html

there's many more, but thought this was interesting, 

  because they are "gov public info" cams

on the traffic cams, 

  i once followed a red convertible full of girls thru town (LOL)

    don't know if you can still do that or not....  

anyway, thought you might like to see and put this in your link files

SYNQ - Video API built for developers

https://www.synq.fm/

The Synq FM is a cloud based Video API

What it can do?

• Simple video upload and storage
• Transcoding into various formats for a variety of platforms
• A customizable, embedded player
• Attaching custom video metadata (like tags, groups, playlists, and so on)
• Webhook notifications for various events
• Geo-local content delivery

Multiple libraries for mobile, web and servers. Use our client libraries for Python, Javascript, iOS, Android and others, or directly through HTTP POST requests.

• JavaScript Client SDK
• Android SDK
• iOS SDK

Automatically switch between several Content Delivery Networks (CDNs) to increase performance and improve user experience.

Magic Leap is actually way behind, like we always suspected it was

http://www.theverge.com/2016/12/8/13894000/magic-leap-ar-microsoft-hololens-way-behind 

Magic Leap’s allegedly revolutionary augmented reality technology may in fact be years away from completion and, as it stands now, is noticeably inferior to Microsoft’s HoloLens headset, according to a report from The Information. The report, which incorporates an interview with Magic Leap CEO Rony Abovitz, reveals that the company posted a misleading product demo last year showcasing its technology. The company has also had trouble miniaturizing its AR technology from a bulky helmet-sized device into a pair of everyday glasses, as Abovitz has repeatedly claimed the finished product will accomplish.

YES MORE BULLSHITTERS, Meanwhile I can't get my several AR startups I'm advising any money because guy like this sucked it all up.

Google Glass Teardown

What's inside Google Glass?

MIT Creates AI Able to See Two Seconds Into the Future

http://www.dailygalaxy.com/my_weblog/2016/11/mit-creates-ai-that-is-able-to-see-two-seconds-into-the-future-on-monday-the-massachusetts-institute-of-technology-announce.html


Massachusetts Institute of Technology announced its new artificial intelligence. Based on a photograph alone, it can predict what’ll happen next, then generate a one-and-a-half second video clip depicting that possible future.


When we see two people meet, we can often predict what happens next: a handshake, a hug, or maybe even a kiss. Our ability to anticipate actions is thanks to intuitions born out of a lifetime of experiences.

Machines, on the other hand, have trouble making use of complex knowledge like that. Computer systems that predict actions would open up new possibilities ranging from robots that can better navigate human environments, to emergency response systems that predict falls, to Google Glass-style headsets that feed you suggestions for what to do in different situations.

This week researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have made an important new breakthrough in predictive vision, developing an algorithm that can anticipate interactions more accurately than ever before.

http://web.mit.edu/vondrick/tinyvideo/paper.pdf

http://web.mit.edu/vondrick/tinyvideo/

Generating Videos with Scene Dynamics

Carl Vondrick
MIT Hamed Pirsiavash
University of Maryland Baltimore County Antonio Torralba
MIT

NIPS 2016

Download Paper

Abstract

We capitalize on large amounts of unlabeled video in order to learn a model of scene dynamics for both video recognition tasks (e.g. action classification) and video generation tasks (e.g. future prediction). We propose a generative adversarial network for video with a spatio-temporal convolutional architecture that untangles the scene's foreground from the background. Experiments suggest this model can generate tiny videos up to a second at full frame rate better than simple baselines, and we show its utility at predicting plausible futures of static images. Moreover, experiments and visualizations show the model internally learns useful features for recognizing actions with minimal supervision, suggesting scene dynamics are a promising signal for representation learning. We believe generative video models can impact many applications in video understanding and simulation.

Build hardware synchronized 360 VR camera with YI 4K action cameras

http://open.yitechnology.com/vrcamera.html

http://www.yijump.com/

YI 4K Action Camera is your perfect pick for building a VR camera. The camera boasts high resolution image detail powered by amazing video capturing and encoding capabilities, long battery life and camera geometry. This is what makes us stand out and how we are recognized and chosen as a partner by Google for its next version VR Camera, Google Jump - www.yijump.com

There are a number of ways to build a VR camera with YI 4K Action Cameras. The difference being mainly how you control multiple cameras to start and stop recordings. In general, we would like all cameras to start and stop recording synchronously so you can easily record and stitch your virtual reality video.

The easiest solution is to manually control the cameras one-by-one. It is convenient and quick however it doesn’t guarantee synchronized recording.

A better solution therefore is to make good use of Wi-Fi where all cameras are set to work in Wi-Fi mode and are connected to a smartphone hotspot or a Wi-Fi router. Once setup is done, you should be able to control all cameras with smartphone app through Wi-Fi. For details, please check out https://github.com/YITechnology/YIOpenAPI

Please note that this solution also comes with its limitations. For instance, when there are way too many cameras or Wi-Fi interference happens to be serious, controlling the cameras via smartphone app can sometimes fail. Also, synchronized video capturing is not guaranteed since Wi-Fi is not a real-time communication protocol.

You can also control all cameras with a Bluetooth-connected remote control. The limitations however are similar to that with Wi-F solution.

There are also solutions which try to synchronize video files offline after recording is finished. It is normally done by detecting the same audio signal or video motion in the video files and aligning them. Since this kind of the solutions do not control the recording start time, its synchronization error is at least 1 frame.

HARDWARE SYNCHRONIZED RECORDING

In this article, we will introduce a solution to solve synchronization problem using hardware. We do this by connecting all cameras using Multi Endpoint cable where recording start and stop commands are transmitted in real-time among the cameras, in turn, creating a high-resolution and synchronized virtual reality video.

Samsung applies for trademark on 'QLED' TVs - FlatpanelsHD

http://www.flatpanelshd.com/news.php?subaction=showfull&id=1467880160


Sent from my iPad

Breathing Life into Shape (SIGGRAPH 2014)

This has serious implications in security, interrogation, marketing, health and medical.



Soon high res 3D Depth cameras will be cheap and common place.

Pinlight Displays: Wide Field of View Augmented Reality Eyeglasses (SIGG...

Slim near eye display using pinhole aperture arrays

Boom, Mike Drop.

This just got trivial.

LOW-COST VIDEO STREAMING WITH A WEBCAM AND RASPBERRY PI

http://hackaday.com/2016/11/25/low-cost-video-streaming-with-a-webcam-and-raspberry-pi/


http://videos.cctvcamerapros.com/raspberry-pi/ip-camera-raspberry-pi-youtube-live-video-streaming-server.html


Spoiler Alert, Basically they use the Raspberry Pi to connect to the CCTV IP camera over RTSP and then send a live stream up to youtube. Up, out though your firewall and NAT to youtube or any service that will accept RTMP.

Most of this is a good NOVICE GUIDE to setting up and configuring the Pi and buying a IP camera from them.

1. You can download the source code for the BASH script here.

#!/bin/bash

SERVICE="ffmpeg"
RTSP_URL="rtsp://192.168.0.119:554/video.pro1"
YOUTUBE_URL="rtmp://a.rtmp.youtube.com/live2"
YOUTUBE_KEY="dn7v-5g6p-1d3w-c3da"

COMMAND="sudo ffmpeg -f lavfi -i anullsrc -rtsp_transport tcp -i ${RTSP_URL} -tune zerolatency -vcodec libx264 -t 12:00:00 -pix_fmt + -c:v copy -c:a aac -strict experimental -f flv ${YOUTUBE_URL}/${YOUTUBE_KEY}"

if sudo /usr/bin/pgrep $SERVICE > /dev/null
then
        echo "${SERVICE} is already running."
else
        echo "${SERVICE} is NOT running! Starting now..."
        $COMMAND
fi

They have a bunch of neat Pi Video projects on their web site.
http://videos.cctvcamerapros.com/raspberry-pi

Chronos 1.4 high-speed camera up to 21,600fps

Chronos 1.4 is a purpose-designed, professional high-speed camera in the palm of your hand. With a 1.4 gigapixel-per-second throughput, you can capture stunning high-speed video at up to 1280x1024 resolution. Frame rate ranges from 1,057fps at full resolution, up to 21,600fps at minimum resolution.

Features and specs

See the full specs in the Chronos 1.4 Datasheet

• 1280x1024 1057fps CMOS image sensor with 1.4Gpx/s throughput
• Higher frame rates at lower resolution (see table below)
• Sensor dimensions 8.45 x 6.76mm, 6.6um pixel pitch
• Global shutter - no “jello” effect during high-motion scenes
• Electronic shutter from 1/fps down to 2us (1/500,000 s)
• CS and C mount lens support
• Focus peaking (focus assist) and zebra exposure indicator
• ISO 320-5120 (Color), 740-11840 (Monochrome) sensitivity
• 5" 800x480 touchscreen (multitouch, capacitive)
• Machined aluminum case
• Record time 4s (8GB) or 8s (16GB)
• Continuous operation on AC adapter (17-22V 40W)
• 1.75h runtime on user-replaceable EN-EL4a battery
• Gigabit ethernet remote control and video download*
• Audio IO and internal microphone*
• HDMI video output*
• Two channel 1Msa/s waveform capture*
• Storage: SD card, two USB host ports (flash drives/hard drives), eSATA 3G
• Trigger: TTL, switch closure, image change*, sound*, accelerometer*
• Low-noise variable-speed fan - camera can run indefinitely without overheating

https://www.kickstarter.com/projects/1714585446/chronos-14-high-speed-camera/description

Pinlight Displays: Wide Field of View Augmented Reality Eyeglasses (SIGG...

OMG! This is so simple. Mind blown.

Read more at:
  http://pinlights.info/

ELP contact info

Maker of USB webcam boards.

Teardown of Voyager HD video camera U845Wifi low cost FPV wifi streaming camera

Fwd: Low-cost, Low-power Neural Networks; Real-time Object Detection and Classification; More

---------- Forwarded message ----------
From: Embedded Vision Insights from the Embedded Vision Alliance <newsletter@embeddedvisioninsights.com>
Date: Tue, Aug 30, 2016 at 7:36 AM
Subject: Low-cost, Low-power Neural Networks; Real-time Object Detection and Classification; More

VOL. 6, NO. 17

A NEWSLETTER FROM THE EMBEDDED VISION ALLIANCE

Late August 2016

To view this newsletter online, please click here

FEATURED VIDEOS

"Tailoring Convolutional Neural Networks for Low-Cost, Low-Power Implementation," a Presentation from Synopsys Deep learning-based object detection using convolutional neural networks (CNN) has recently emerged as one of the leading approaches for achieving state-of-the-art detection accuracy for a wide range of object classes. Most of the current CNN-based detection algorithm implementations run on high-performance computing platforms that include high-end general-purpose processors and GP-GPUs. These CNN implementations have significant computing power and memory requirements. Bruno Lavigueur, Project Leader for Embedded Vision at Synopsys, presents the company's experience in reducing the complexity of the CNN graph to make the resulting algorithm amenable to low-cost and low-power computing platforms. This involves reducing the compute requirements, memory size for storing convolution coefficients, and moving from floating point to 8 and 16 bit fixed point data widths. Lavigueur demonstrates results for a face detection application running on a dedicated low-cost and low-power multi-core platform optimized for CNN-based applications. "An Augmented Navigation Platform: The Convergence of ADAS and Navigation," a Presentation from Harman Until recently, advanced driver assistance systems (ADAS) and in-car navigation systems have evolved as separate standalone systems. Today, however, the combination of available embedded computing power and modern computer vision algorithms enables the merger of these functions into an immersive driver information system. In this presentation, Alon Atsmon, Vice President of Technology Strategy at Harman International, discusses the company's activities in ADAS and navigation. He explores how computer vision enables more intelligent systems with more natural user interfaces, and highlights some of the challenges associated with using computer vision to deliver a seamless, reliable experience for the driver. Atsmon also demonstrates Harman's latest unified Augmented Navigation platform which overlays ADAS warnings and navigation instructions over a camera feed or over the driver's actual road view. More Videos

FEATURED ARTICLES

A Design Approach for Real Time Classifiers Object detection and classification is a supervised learning process in machine vision to recognize patterns or objects from images or other data, according to Sudheesh TV and Anshuman S Gauriar, Technical Leads at PathPartner Technology. It is a major component in advanced driver assistance systems (ADAS), for example, where it is commonly used to detect pedestrians, vehicles, traffic signs etc. The offline classifier training process fetches sets of selected images and other data containing objects of interest, extracts features from this input, and maps them to corresponding labelled classes in order to generate a classification model. Real-time inputs are categorized based on the pre-trained classification model in an online process which finally decides whether or not the object is present. More Pokemon Go-es to Show the Power of AR Pokemon Go is an awesome concept, says Freddi Jeffries, Content Marketer at ARM. While she's a strong believer in VR (virtual reality) as a driving force in how we will handle much of our lives in the future, she can now see that apps like this have the potential to take AR (augmented reality) mainstream much faster than VR. More More Articles

FEATURED NEWS

Intel Announces Tools for RealSense Technology Development Auviz Systems Announces Video Content Analysis Platform for FPGAs Sighthound Joins the Embedded Vision Alliance Qualcomm Helps Make Your Mobile Devices Smarter with New Snapdragon Machine Learning Software Development Kit Basler Addressing the Industry´s Hot Topics at VISION Stuttgart More News

UPCOMING INDUSTRY EVENTS

ARC Processor Summit: September 13, 2016, Santa Clara, California Deep Learning for Vision Using CNNs and Caffe: A Hands-on Tutorial: September 22, 2016, Cambridge, Massachusetts IEEE International Conference on Image Processing (ICIP): September 25-28, 2016, Phoenix, Arizona SoftKinetic DepthSense Workshop: September 26-27, 2016, San Jose, California Sensors Midwest (use code EVA for a free Expo pass): September 27-28, 2016, Rosemont, Illinois Embedded Vision Summit: May 1-3, 2017, Santa Clara, California

Embedded Vision Alliance · 1646 North California Blvd., Suite 220 · Walnut Creek, California 94596 · USA