Object Detection in Dynamic Scenes Based on Codebook with Superpixels

This paper proposed a new object detection method based on codebook with super pixels (CBSP-OD), which overcomes large memory requirements, calculated quantity problems and code words created are not exact in dynamic scenes. The CBSP-OD algorithm converts pixels from RGB space to HSL space and cluster pixels into super pixels. In this way, we just use L component as light value to reduce computational complexity and enforce robust to light. CBSP-OD use super pixel instead of single pixel to build background model, in which consider spatial consistency well and create code words more exactly. And then, build code words on every super pixel. In this way, large memory requirements and calculated quantity problems can be avoided. Experiments in the dynamic scenes demonstrate the proposed method outperform recent state-of the-art methods.