In this paper, we propose a new visual object tracking approach via one-class SVM (OC-SVM), inspired by the fact that OC-SVM’s support vectors can form a hyper-sphere, whose center can be regarded as a robust object estimation from samples. In the tracking approach, a set of tracking samples are constructed in a predefined searching window of a video frame. And then a threshold strategy is prop...

When errors are introduced into a compressed image or video bitstream, blocks of pixels are lost. The decoder attempts to conceal this loss to maximize displayed picture quality. We discuss a few different conditions under which satisfactory interpolation of the missing blocks is possible. For images, these conditions include situations where the image is locally smooth or locally one dimension...

In this paper we present a new method to compute frame based audio similarities, based on nearest neighbour density estimation. We do not recommend it is as a practical method for large collections because of the high runtime. Rather, we use this new method for a detailed analysis to get a deeper insight on how a bag of frames approach (BOF) determines similarities among songs, and in particula...

Aiming at the traditional Gaussian mixture model has poor adaptability to the complex scenes, we proposes an improved moving object detection algorithm based on Gaussian mixture model and HSV space. The motion region is first extracted by the improved three-frame difference method. With the matching results, region segmentation of current frame is realized. Then different regions adopt differen...