Object detection using Hough transform and Conditional Random Field model

Hough transform provides a different and effective way for object detection. This approach has attracted much attention since the implicit shape model (ISM) was proposed. Inspired by the Implicit Shape Model and Conditional Random Field (CRF), we present in this paper a conditional probabilistic model to formulate the relationship between the voting elements and the hypotheses in the Hough transform. Based on this model, an efficient object detection scheme is proposed and experimental results demonstrate the effectiveness of the proposed scheme.