In this paper, we introduce a novel real-time tracker based on color, texture and motion information. RGB color histogram and correlogram (autocorrelogram) are exploited as color cues and texture properties are represented by local binary patterns (LBP). Object's motion is taken into account through location and trajectory. After extraction, these features are used to build a unifying distance measure. The measure is utilized in tracking and in the classification event, in which an object is leaving a group. The initial object detection is done by a texture-based background subtraction algorithm. The experiments on indoor and outdoor surveillance videos show that a unified system works better than the versions based on single features. It also copes well with low illumination conditions and low frame rates which are common in large scale surveillance systems.
Takala et al. REF represented colour cues and texture properties with local binary patterns to build a unifying distance measure, which is subsequently used for tracking and event classification.
Multi-Object Tracking Using Color, Texture and Motion
2007 IEEE Conference on Computer Vision and Pattern Recognition
2007 IEEE Conference on Computer Vision and Pattern Recognition
Computer Science