The Coming Era of Egocentric Video Analysis
From the post:
Head-mounted cameras are becoming de rigueur for certain groups—extreme sportsters, cyclists, law enforcement officers, and so on. It’s not hard to find content generated in this way on the Web.
So it doesn’t take a crystal ball to predict that egocentric recording is set to become ubiquitous as devices such as Go-Pros and Google Glass become more popular. An obvious corollary to this will be an explosion of software for distilling the huge volumes of data this kind of device generates into interesting and relevant content.
Today, Yedid Hoshen and Shmuel Peleg at the Hebrew University of Jerusalem in Israel reveal one of the first applications. Their goal: to identify the filmmaker from biometric signatures in egocentric videos.
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A tidbit that I was unaware of:
Some of these are unique, such as the gait of the filmmaker as he or she walks, which researchers have long known is a remarkably robust biometric indicator.”Although usually a nuisance, we show that this information can be useful for biometric feature extraction and consequently for identifying the user,” say Hoshen and Peleg.
Makes me wonder if I should wear a prosthetic device to alter my gait when I do appear in range of cameras. 😉
Works great with topic maps. All you may know about an actor is that they have some gait with X characteristics. And a perchance for not getting caught planting explosive devices. With a topic map we can keep their gait as a subject identifier and record all the other information we have on such an individual.
If we ever match the gait to a known individual, then the information from both records, both as the anonymous gait owner and the known known individual will be merged together.
It works with other characteristics as well, which enables you to work from “I was attacked…,” to more granular information that narrows the pool of suspects down to a manageable size.
Traditionally the job of veterans on the police force who know their communities and who are the usual suspects but a topic map enhances their value by capturing their observations for use by the department long after a veterans retirement.
From arXiv: Egocentric Video Biometrics
Abstract:
Egocentric cameras are being worn by an increasing number of users, among them many security forces worldwide. GoPro cameras already penetrated the mass market, and Google Glass may follow soon. As head-worn cameras do not capture the face and body of the wearer, it may seem that the anonymity of the wearer can be preserved even when the video is publicly distributed.
We show that motion features in egocentric video provide biometric information, and the identity of the user can be determined quite reliably from a few seconds of video. Biometrics are extracted by training Convolutional Neural Network (CNN) architectures on coarse optical flow.Egocentric video biometrics can prevent theft of wearable cameras by locking the camera when worn by people other than the owner. In video sharing services, this Biometric measure can help to locate automatically all videos shot by the same user. An important message in this paper is that people should be aware that sharing egocentric video will compromise their anonymity.
Now if we could just get members of Congress to always carry their cellphones and wear body cameras.