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Current and upcoming wide-area aerial video collectors have very large effective focal plane arrays, and can generate a tremendous amount of data. This presents significant challenges for onboard storage and for real-time downlink. This paper presents the results of an evaluation of a number of different image and video compression schemes on wide-area video. In general, we found that video compression...
The iris is a highly accurate biometric identifier. However widespread adoption is hindered by the difficulty of capturing high-quality iris images with minimal user co-operation. This paper describes a first-generation prototype iris identification system designed for stand-off cooperative access control. This system identifies individuals who stand in front of and face the system after 3.2 seconds...
Existing approaches to detect modeled activities in video often require the precise specification of the number of actors or roles, or spatial constraints, or other limitations that create difficulties for generic detection of group activities. We develop an approach to detect group behaviors in video, where an arbitrary number of participants are involved. We address scene conditions with non-participating...
We present a novel approach to learning motion behavior in video, and detecting abnormal behavior, using hierarchical clustering of hidden Markov models (HMMs). A continuous stream of track data is used for online and on-demand creation and training of HMMs, where tracks may be of highly variable length and scenes may be very complex with an unknown number of motion patterns. We show how these HMMs...
As video tracking research matures, the issue of tracker performance evaluation has emerged as a research topic in its own right, as evidenced by a series of workshops devoted solely to this purpose (the workshops on performance evaluation of tracking and surveillance-PETS). However, evaluations such as PETS have been limited to small scenarios with a handful of moving objects. In this paper, we present...
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