Improved Pairwise Max Suppression Considering Total Number of Targets
Ryusuke Miyamoto, Shingo Kobayashi, Takuro Oki, Hiroyuki Yomo, Shinsuke Hara · 2018
The authors try to construct a novel sensor networking scheme that obtains the location of sensor nodes using image processing in order to enable dynamic routing when the speed and the density of the sensor nodes become high. In this scheme, visual object detection is applied for the localization of sensor nodes; however, certain failures occur during the region merging process, which is required for schemes based on sliding windows. For the widely used pairwise max suppression(PMS), the most significant problem is the fixed threshold for region merging. To solve this problem, this paper proposes a novel scheme for region merging that adopts adaptive thresholding for the existing PMS. The threshold is appropriately determined by taking into account the total number of detection targets. The experimental results, conducted using a dataset composed of top-view images generated from a CG-based virtual space, showed that the miss rate can be reduced to approximately 67.4% of the existing PMS.