Mass. DAs adopt Salient Stills for crime scene video processing
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John,
Salient Stills today announced the MDAA - Massachusetts District Attorneys Association - has adopted the company’s video forensics system to secure, capture, and process evidence from crime scene videos. This frees the DAs from relying on other law enforcement agency crime labs to conduct video forensics, and enables seven of the 11 MDAA offices to more quickly process video evidence and advance investigations, arrests and prosecutions.
Background – The MDAA, headquartered in downtown Boston, is an independent state agency that supports the eleven elected Massachusetts District Attorneys and their combined staff of 1,500 employees, who collectively prosecute approximately 300,000 cases annually. Funding for the systems was provided by a U.S. Department of Justice (DOJ) Community Oriented Policing Services (COPS) technology grant.
SALIENT STILLS SUPPORTS MASSACHUSETTS DISTRICT ATTORNEYS
DAs Conduct Video Forensics With VideoFOCUS Pro
BOSTON, August 8, 2011 - Salient Stills, the leader in video forensics and image enhancement, today announced the Massachusetts District Attorneys Association (MDAA) has licensed VideoFOCUS Pro to seven of the eleven Massachusetts DA offices, enabling its members to conduct hands on video forensics to secure, capture, and process evidence from video samples. Funding for the systems was awarded to the MDAA by a U.S. Department of Justice (DOJ) Community Oriented Policing Services (COPS) technology grant.
More and more investigations and prosecutable cases have videos as part of the evidence. Unfortunately, these videos can be of poor quality, hard to export from proprietary security camera systems, and combined with other video streams, making it difficult to locate, isolate and extract the most helpful sequences and stills, said Pat Alfieri, Chief Information Officer for MDAA. By deploying VideoFOCUS Pro among our members, the DAs and their investigators can quickly process video evidence and advance investigations, arrests and prosecutions.
“Video forensics is a powerful tool for law enforcement agencies, helping them identify suspects and place them at the scene of a crime, establishing a chain of events, and, ultimately, supporting successful prosecutions,” said Laura Teodosio, president and CEO of Salient Stills. “With access to the latest video forensics technology in VideoFOCUS Pro, local DAs can process video faster, freeing time for other important activities.”
MDAA is an independent state agency that supports the eleven elected Massachusetts District Attorneys and their combined staff of 1,500 employees, who collectively prosecute approximately 300,000 cases annually. The agency manages statewide business technology services and administers grants in the areas of Violence Against Women, Motor Vehicle Crimes, and federal technology grants. MDAA also produces publications for prosecutors and victim-witness advocates, hosts dozens of prosecutor trainings annually, and provides information on budgetary, criminal justice and public safety issues to the executive and legislative branches.
Designed for use by law enforcement officers and using innovative processing algorithms, VideoFOCUS Pro dramatically improves the ability to capture and export fuzzy or grainy video from videotape, CCTV systems, digital video cameras, cell phones and proprietary DVR formats. The system generates higher resolution stills and videos to help identify suspects and produce other leads. VideoFOCUS Pro is in use by hundreds of investigative agencies in over 20 countries and throughout the United States.
About Salient Stills Founded in 1997, Salient Stills is a leading video forensics and image enhancement software company. Salient Stills introduced its technology to answer the need for an efficient and effective video image enhancement solution. VideoFOCUS Pro and VF Source are video forensics solutions in use by law enforcement, security and military and intelligence agencies. For more information on Salient Stills visit www.salientstills.com.
Salient Stills today announced the MDAA - Massachusetts District Attorneys Association - has adopted the company’s video forensics system to secure, capture, and process evidence from crime scene videos. This frees the DAs from relying on other law enforcement agency crime labs to conduct video forensics, and enables seven of the 11 MDAA offices to more quickly process video evidence and advance investigations, arrests and prosecutions.
Background – The MDAA, headquartered in downtown Boston, is an independent state agency that supports the eleven elected Massachusetts District Attorneys and their combined staff of 1,500 employees, who collectively prosecute approximately 300,000 cases annually. Funding for the systems was provided by a U.S. Department of Justice (DOJ) Community Oriented Policing Services (COPS) technology grant.
"Technology Review reports on a startup with software used by stores to track, count and log people captured by security cameras. Prism Skylab's technology can produce heatmaps showing where people went and produce other statistics that the company claims offer tracking and analytics like those used online for the real world. One use case is for businesses to correlate online promotions and deals — such as Groupon offers — with real world footfall and in-store behavior."
"H-Online reports that 'researchers at the Münster University of Applied Sciences have discovered that it is possible to use electricity usage data from smart electricity meters to determine which programmes consumers are watching on a standard TV set. By analysing electricity consumption patterns, it is, in principle, also possible to identify films played from a DVD or other source.' It's time for some clever EEs to come up with a countermeasure. Unfortunately alumfoil hats have already been dismissed."
MIT researcher Deb Roy wanted to understand how his infant son learned language -- so he wired up his house with videocameras to catch every moment (with exceptions) of his son's life, then parsed 90,000 hours of home video to watch "gaaaa" slowly turn into "water." Astonishing, data-rich research with deep implications for how we learn.
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From Transcript around 11:40 in to it:
In my lab, which we're peering into now, at MIT -- this is at the media lab. This has become my favorite way of videographing just about any space. Three of the key people in this project, Philip DeCamp, Rony Kubat and Brandon Roy are pictured here. Philip has been a close collaborator on all the visualizations you're seeing. And Michael Fleischman was another Ph.D. student in my lab who worked with me on this home video analysis, and he made the following observation: that "just the way that we're analyzing how language connects to events which provide common ground for language, that same idea we can take out of your home, Deb, and we can apply it to the world of public media." And so our effort took an unexpected turn.
Think of mass media as providing common ground and you have the recipe for taking this idea to a whole new place. We've started analyzing television content using the same principles -- analyzing event structure of a TV signal -- episodes of shows, commercials, all of the components that make up the event structure. And we're now, with satellite dishes, pulling and analyzing a good part of all the TV being watched in the United States. And you don't have to now go and instrument living rooms with microphones to get people's conversations, you just tune into publicly available social media feeds.
So we're pulling in about three billion comments a month. And then the magic happens. You have the event structure, the common ground that the words are about, coming out of the television feeds; you've got the conversations that are about those topics; and through semantic analysis -- and this is actually real data you're looking at from our data processing -- each yellow line is showing a link being made between a comment in the wild and a piece of event structure coming out of the television signal. And the same idea now can be built up. And we get this wordscape, except now words are not assembled in my living room. Instead, the context, the common ground activities, are the content on television that's driving the conversations. And what we're seeing here, these skyscrapers now, are commentary that are linked to content on television. Same concept, but looking at communication dynamics in a very different sphere.
And so fundamentally, rather than, for example, measuring content based on how many people are watching, this gives us the basic data for looking at engagement properties of content. And just like we can look at feedback cycles and dynamics in a family, we can now open up the same concepts and look at much larger groups of people. This is a subset of data from our database -- just 50,000 out of several million -- and the social graph that connects them through publicly available sources. And if you put them on one plain, a second plain is where the content lives. So we have the programs and the sporting events and the commercials, and all of the link structures that tie them together make a content graph. And then the important third dimension. Each of the links that you're seeing rendered here is an actual connection made between something someone said and a piece of content. And there are, again, now tens of millions of these links that give us the connective tissue of social graphs and how they relate to content. And we can now start to probe the structure in interesting ways.
So if we, for example, trace the path of one piece of content that drives someone to comment on it, and then we follow where that comment goes, and then look at the entire social graph that becomes activated and then trace back to see the relationship between that social graph and content, a very interesting structure becomes visible. We call this a co-viewing clique, a virtual living room if you will. And there are fascinating dynamics at play. It's not one way. A piece of content, an event, causes someone to talk. They talk to other people. That drives tune-in behavior back into mass media, and you have these cycles that drive the overall behavior.
Another example -- very different -- another actual person in our database -- and we're finding at least hundreds, if not thousands, of these. We've given this person a name. This is a pro-amateur, or pro-am, media critic who has this high fan-out rate. So a lot of people are following this person -- very influential -- and they have a propensity to talk about what's on TV. So this person is a key link in connecting mass media and social media together.
One last example from this data: Sometimes it's actually a piece of content that is special. So if we go and look at this piece of content, President Obama's State of the Union address from just a few weeks ago, and look at what we find in this same data set, at the same scale, the engagement properties of this piece of content are truly remarkable. A nation exploding in conversation in real time in response to what's on the broadcast. And of course, through all of these lines are flowing unstructured language. We can X-ray and get a real-time pulse of a nation, real-time sense of the social reactions in the different circuits in the social graph being activated by content.
So, to summarize, the idea is this: As our world becomes increasingly instrumented and we have the capabilities to collect and connect the dots between what people are saying and the context they're saying it in, what's emerging is an ability to see new social structures and dynamics that have previously not been seen. It's like building a microscope or telescope and revealing new structures about our own behavior around communication. And I think the implications here are profound, whether it's for science, for commerce, for government, or perhaps most of all, for us as individuals.
The primary audience is coaches and athletes to study and optimize biomechanics.
Used by athletic coaches to breakdown and analyze the movements as well as categorize videos to create an index of events (e.g. pass goal, player, Golf Swing, Runner Stride, etc).
Video Analytics is a technology that is used to analyze video for specific data, behavior, objects or attitude. It has a wide range of applications including safety and security.
"The US military is inundated with video from airborne unmanned aircraft, remote monitoring systems and security outposts. In an effort to speed up the processing and analyzing of all this video, researchers at Defense Advanced Research Projects Agency (DARPA) this week awarded an almost $11 million contract to open source software vendor Kitware to help develop what DARPA calls its Video and Image Retrieval and Analysis Tool (VIRAT) program."
"Here's a a demonstration video of EmoRate, a software program that uses the Emotiv 14-electrode EEG headset to record your emotions via your facial expressions. In the video you'll see EmoRate record my emotions while I watch a YouTube video, then index that video by emotion, and then navigate that video by simply by remembering a feeling. The web page for EmoRate explains how I used Emotiv's SDK to build the software program, and how I trained the system by watching emotionally evocative videos on YouTube while wearing the headset."
"A computer vision research group at UCLA has put together a system that watches surveillance footage and generates a text description of the events in real time. It only works on traffic cameras for now but demonstrates how sophisticated computer vision is becoming. Interestingly, the system was built thanks to a database of millions of human-labeled images put together by Chinese workers."
Zhu and UCLA colleagues Benjamin Yao and Haifeng Gong developed a new system, called I2T (Image to Text) puts a series of computer vision algorithms into a system that takes images or video frames as input, and spits out summaries of what they depict. "That can be searched using simple text search, so it's very human-friendly," says Zhu.
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