Dairy goat detection based on Faster R-CNN from surveillance video

As one of the most famous algorithms, Faster R-CNN has been applied to many fields. However, it is unlikely to be used to surveillance videos directly because of its low efficiency and precision. To deal with these problems, this paper puts forward an object detection method which is based on Faster CNN to detect dairy goats in the surveillance video. It includes key frames extraction, foreground segmentation, region proposal and Fast R-CNN. The experimental results show that our method is more than twice as fast as Faster R-CNN and obtains 92.49% average precision. Our results suggest that our key frame extraction and region proposal method are helpful for detecting dairy goats.