title: Biologically inspired scene context for object detection using a single instance.
abstract: This paper presents a novel object detection method using a single instance from the object category. Our method uses biologically inspired global scene context criteria to check whether every individual location of the image can be naturally replaced by the query instance, which indicates whether there is a similar object at this location. Different from the traditional detection methods that only look at individual locations for the desired objects, our method evaluates the consistency of the entire scene. It is therefore robust to large intra-class variations, occlusions, a minor variety of poses, low-revolution conditions, background clutter etc., and there is no off-line training. The experimental results on four datasets and two video sequences clearly show the superior robustness of the proposed method, suggesting that global scene context is important for visual detection/localization.
authors.affiliation: Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Changxin
authors.initials: C
authors.lastname: Gao
authors.affiliation: Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Nong
authors.initials: N
authors.lastname: Sang
authors.affiliation: Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Rui
authors.initials: R
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D010364:Pattern Recognition, Visual / Q000502:physiology; D014796:Visual Perception / Q000502:physiology