Abstract
To solve the problem that the positioning strategy with sliding window approaches requires exhaustive search in feature pyramids, the paper proposes an object detection algorithm based on deformable part models with Bing features to help object detection. First of all, input images are preprocessed with the objectness detection algorithm with Bing features and a set of potential windows that may contain target objects are obtained, and then the deformable part model is regarded as the class-specific detector to match potential windows, at last Non-Maximum Suppression is used to merge and reduce window areas of results to obtain final detection results. The experimental results on Pascal VOC 2007 dataset show that the algorithm in the paper outperforms the original DPM in 19 out of 20 classes, achieving an improvement of 2.7% mAP.
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