We present a fast and robust method for moving object tracking directly in the compressed domain using features available in MPEG videos. DCT domain background subtraction in Y pla...
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
We derive a probabilistic framework for robust, real-time, visual tracking of previously unseen objects from a moving camera. The tracking problem is handled using a bag-of-pixels ...
This paper presents a computer vision system for tracking and predicting flying balls in 3-D from a stereo-camera. It pursues a “textbook-style” approach with a robust circle ...
This article proposes a local photometric model that compensates for specular highlights and lighting variations due to position and intensity changes. We define clearly on which ...