A novel method for object detection based on graph theory

International Journal of Physical Sciences

Shu Zhang¹ 

关键词: Object detection;    graph cut;    sliding window;    locality-constrained linear coding (LLC);    support vector machine (SVM).;   

DOI  :  10.5897/IJPS11.1132

学科分类：物理（综合）

来源: Academic Journals

【 摘 要 】

Ideal object detection result in an image is an optimal free shape sub-window thattightly covers the object of interest.However, the sub-windows considered in widely-used sliding window method are limited to rectangles. This paper proposed a new graph-theoretic method which allowed the detection sub-window to be any shape for object detection. Firstly, local features responses were calculated by using locality-constrained linear coding (LLC) technique. Then the proposed method take advantage of local feature response and boundary information to construct an objective function for the whole image and global optimal solution is obtained by graph cut algorithm. We provided results on two challenging object detection datasets, and demonstrated that the proposed method can obtained better spatial support and higher detection precision than existing sliding window method.

【 授权许可】

CC BY