Abstract: Sliding window detectors need to compute overall scores on all the positions and scales in the image pyramid, which causes the detection speed to be relatively slow. In order to accelerate the detection speed, we propose a candidate points' detection algorithm for deformable part models. Multiple segmentation algorithms are used for each image to generate image segments. The segment's top-left corner is treated as a candidate detection point. We adapt mixture deformable part models as our underlying detectors. The detection operations are only carried on these candidate detection points to accelerate detection speed dramatically. We evaluate the detection performance of our approach on PASCAL 2007 challenge dataset and find that the candidate points' detection is even better than exhaustive search.