We present an unsupervised technique for detecting unusual activity in a large video set using many simple features. No complex activity models and no supervised feature selection...
This paper deals with the fully automatic extraction of classifiable person features out of a video stream with challenging background. Basically the task can be split in two part...
This paper presents the design of an embedded automated digital video surveillance system with real-time performance. Hardware accelerators for video segmentation, morphological op...
Fredrik Kristensen, Hugo Hedberg, Hongtu Jiang, Pe...
The rate-distortion optimal mode decision as well as motion estimation adopted in H.264 brings a big challenge to realtime encoding and transcoding duo to the high computation com...
Yi Wang, Xiaoyan Sun, Feng Wu, Shipeng Li, Houqian...
In this paper, we address the problem of automatically detecting and tracking a variable number of persons in complex
scenes using a monocular, potentially moving, uncalibrated ca...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...