Object tracking through multiple cameras is a popular research topic in security and surveillance systems especially when human objects are the target. However, occlusion is one of the challenging problems for the tracking process. This paper proposes a multiple-camera-based cooperative tracking method to overcome the occlusion problem.  The paper presents a new model for combining convolutiona...

Cross-correlator plays a significant role in many visual perception tasks, such as object detection and tracking. Beyond the linear cross-correlator, this paper proposes a kernel crosscorrelator (KCC) that breaks traditional limitations. First, by introducing the kernel trick, the KCC extends the linear crosscorrelation to non-linear space, which is more robust to signal noises and distortions....

Most of the tracking methods try to build up feature spaces to represent the appearance of the target. However, limited by the complex structure of the distribution of features, the feature spaces constructed in a linear manner cannot characterize the nonlinear structure well. We propose an appearance model based on kernel ridge regression for visual tracking. Dense sampling is fulfilled around...

This paper presents a technique to robustly compare two distributions represented by samples, without explicitly estimating the density. The method is based on mapping the distributions into a reproducing kernel Hilbert space, where eigenvalue decomposition is performed. Retention of only the top M eigenvectors minimizes the effect of noise on density comparison. A sample application of the tec...

Regularities, or the conformity to unifying principles, are essential to the comprehensibility, manageability and reliability of large software systems, and should, therefore, be considered an important element of their architecture. But the inherent globality of regularities makes them very hard to implement in traditional methods. We have argued previously that this di culty can be alleviated...

Object tracking is an indispensable ingredient of many machine vision applications such as intelligent visual surveillance, traffic monitoring, robot and vehicle navigation, human computer interactions, virtual and augmented realities, video compression and indexing, etc. and has drawn considerable attention from computer research communities in recent years. Actually, in the real world scenari...

Automated motion detection and tracking is a challenging task in traffic surveillance. In this paper, a system is developed to gather useful information from stationary cameras for detecting moving objects in digital videos. The moving detection and tracking system is developed based on optical flow estimation together with application and combination of various relevant computer vision and ima...

The integral histogram for images is an efficient preprocessing method for speeding up diverse computer vision algorithms including object detection, appearance-based tracking, recognition and segmentation. Our proposed Graphics Processing Unit (GPU) implementation uses parallel prefix sums on row and column histograms in a cross-weave scan with high GPU utilization and communication-aware data...