We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
This work proposes a biologically inspired approach to integrate latent topic model with saliency detection. Firstly, a saliency detection algorithm is presented to discriminate s...
Zhidong Li, Yang Wang, Jing Chen, Jie Xu, John Lai...
The popularity and bandwidth consumption attributed to current Peer-to-Peer file-sharing applications makes the operation of these distributed systems very important for the Inte...
Recently, the generative modeling approach to video segmentation has been gaining popularity in the computer vision community. For example, the flexible sprites framework has been...