Object Representation Fusing Global and Local Features

Abstract

In the actual complex scenes, multi-feature fusion has become a valid method of object representation for tracking video motion targets. Two keys about multi-feature fusion are how to select some valid features and how to fuse the features. In this paper, we propose an object representation fusing global and local features for object tracking. In our method, we select a common hue histogram as the global feature and use a valid SIFT feature as the local feature. In the tracking frame of particle filter, the tracking results show that our proposed object representation can better restrain the disturbing of complex environments with abrupt illumination and partial occlusion, than color-based global representation.