Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
In this paper we discuss object detection when only a small number of training examples are given. Specifically, we show how to incorporate a simple prior on the distribution of n...
The existing methods for offline training of cascade classifiers take a greedy search to optimize individual classifiers in the cascade, leading inefficient overall performance. W...
This paper studies image alignment, the problem of learning a shape and appearance model from labeled data and efficiently fitting the model to a non-rigid object with large varia...
Xiaoming Liu 0002, Ting Yu, Thomas Sebastian, Pete...
Visual surveillance applications such as object identification, object tracking, and anomaly detection require reliable motion detection as an initial processing step. Such a dete...