Person Identification from Contextual Motion
We consider the problem of identifying people based on their motion styles. We present a generative model describing the action instance creation process and derive a probabilistic identity inference scheme for two common person identification scenarios motivated by the surveillance and authentication applications. We introduce a novel, \emph{interactive}, scenario for person identification from motion patterns. To this end, we formalize the identification process in the context of a sequential message exchange session between the subject and the system. The subject's behavior is modeled using a probabilistic generative model inspired by the Human Information Processing (HIP) paradigm. At...
| Authors | Igor Kviatkovsky, Ehud Rivlin, Ilan Shimshoni |
|---|---|
| Primary category | cs.CV |
| Published | 11 June 2026 |
| Last updated at source | 11 June 2026 |
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