Performance evaluation of object detection and tracking method under illumination variation

TLDR: Experiments shows that proposed discrete wavelet transform based method has a high capability to detect and track non-rigid moving object, even when light intensities change abruptly.

Abstract: A robust, meticulous and high performance approach is still a great challenge in tracking approach. There are various difficulties in object tracking like noise in scene, illumination changes, occlusion effect, and pose variation into the scene. As an object moves, it changes its orientation relative to the light sources which illuminate it. An illumination variation causes tracking algorithm to lose the target in the scene. This paper presents a discrete wavelet transform based method of detecting and tracking moving object under varying illumination condition with a stationary camera. Discrete wavelet transform provides illumination invariant feature extraction method using gaussian smoothing function and thresholding. We have tested tracking results, on number of video sequences with indoor and outdoor environments and demonstrated the effectiveness of our proposed method. Experiments shows that proposed method has a high capability to detect and track non-rigid moving object, even when light intensities change abruptly.