Abstract
The object recognition method based on local features is significant in computer vision. However, the robustness of this method is limited, since it is often sensitive to large intra-class variance, occlusion, insignificant variety of poses, low-revolution conditions, background clutter etc. Context information gives an access to resolve this problem. Local feature context, object context and scene context can be used in computer vision system. This chapter focuses on the first one, and presents two object recognition approaches with two different types of local context: neighbour-based context and geometric context. Our experimental results demonstrated the good performance of our methods.
Keywords: Object recognition, neighbor-based context, geometric context, part-based representation, keypoints.
