Pixel-wise object tracking

Using a Novel Concept of Potential Pixel Energy for Object Tracking

Abstract   In this paper, we propose a new method for kernel based object tracking which tracks the complete non rigid object. Definition the union image blob and mapping it to a new representation which we named as potential pixels matrix are the main part of tracking algorithm. The union image blob is constructed by expanding the previous object region based on the histogram feature. The pote...

Object Tracking via Pixel-Wise and Block-Wise Sparse Representation

A novel kernel-PLS method for object tracking

In this paper, we propose a On-line kernel-PLS approach to improving both the robustness and accuracy of object tracking which is appropriate for real-time video surveillance. Typical tracking with color histogram matching provides robustness but has insufficient accuracy, because it does not involve spatial information. On the other hand, tracking with pixel-wise matching achieves accurate per...

Using Dominant Sets for Object Tracking with Freely Moving Camera

Object tracking with freely moving cameras is an open issue, since background information cannot be exploited for foreground segmentation, and plain feature tracking is not robust enough for target tracking, due to occlusions, distractors and object deformations. In order to deal with such challenging conditions a traditional approach, based on Camshift-like color-based features, is augmented b...

Moving Objects Tracking Using Statistical Models

Object detection plays an important role in successfulness of a wide range of applications that involve images as input data. In this paper we have presented a new approach for background modeling by nonconsecutive frames differencing. Direction and velocity of moving objects have been extracted in order to get an appropriate sequence of frames to perform frame subtraction. Stationary parts of ...