by Paul Brewer

If you ask security directors how they go back into the video archives to search for something abnormal or for a specific event, the answer is almost always, “I don’t.”  Unless they know which camera feed to watch, and have a fairly good idea of the when to start searching in the video, this manual task is just too daunting. 

Video analytics has brought some much needed automation to this problem.  Now if you know where the event of interest occurred and can create a tripwire or other event rule, then all you have to do is to scroll through the alert logs and jump to that point in the video feed.

That’s great as far as it goes, but it’s still pretty limited.

What do users really want?  Based on direct user feedback, they want to be able to search for specific people, vehicles or events across the enterprise video system.  They want to use what they learn from one search to refine the next.  They want to search by example—designating a specific vehicle or person of interest to flag in a database search that might be narrowed by a specific geographic region or time period.  They want to create searches and visualize search results on an intuitive geo-interface.  And, they don’t want to just be limited to the video archives.  Forensic search results need to then become the parameters for real-time rules to find exactly where that white cargo van of interest is right now. 

This is the future of video search and it is what we are demonstrating right now for our sponsors in the Department of Defense.  A recent field exercise allowed ObjectVideo to showcase the ability to visually “fingerprint” cars that were flagged by HUMINT (human intelligence) and pick them out of the video feeds to present ultra high resolution snapshots to the “Battle Captain.” 

This was not a carefully controlled lab experiment with rigidly scripted scenarios with a small set of total vehicles.  This was a real needle-in-the-haystack exercise with a very small number of “opposition” vehicles operating on crowded public streets.  These vehicles were controlled by an opposition commander with purposes known only to him.

Besides being a great chance to show off what we can currently do with this technology, it was a priceless opportunity to learn from users and hone some new interface and workflow ideas.  When it comes to video search, the best days are still ahead, and possibly not as far off as you might think.

Please share!

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One Response to “in search of…better search”

  1. 增强视觉 | 计算机视觉 增强现实 » 没时间更新的结果就是这样的链接大放送 Says:

    [...] BlogOV的更新,探讨一下智能监控中视频检索的问题。其中谈到的用户需求值得学习。 What do users really want? Based on direct user feedback, they want to be able to search for specific people, vehicles or events across the enterprise video system. They want to use what they learn from one search to refine the next. They want to search by example—designating a specific vehicle or person of interest to flag in a database search that might be narrowed by a specific geographic region or time period. They want to create searches and visualize search results on an intuitive geo-interface. And, they don’t want to just be limited to the video archives. Forensic search results need to then become the parameters for real-time rules to find exactly where that white cargo van of interest is right now. [...]

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