Part of Advances in Neural Information Processing Systems 14 (NIPS 2001)
The most popular algorithms for object detection require the use of exhaustive spatial and scale search procedures. In such approaches, an object is defined by means of local features. fu this paper we show that including contextual information in object detection pro(cid:173) cedures provides an efficient way of cutting down the need for exhaustive search. We present results with real images showing that the proposed scheme is able to accurately predict likely object classes, locations and sizes.