周辺特徴抽出とSoft-NMSによる隠蔽に強い物体検出の検討

抄録

Visual object detection (cars, pedestrians, etc.) from vehicle mounted camera faces great difficulty when the target objects are mutually occluded or partially hidden behind background objects. In this paper, in order to realize a occlusion-robust object detector, we propose to use 1) MDCN¹⁾, a SSD²⁾-based detector which utilizes contextual information surrounding the target objects, together with 2) Soft-NMS³⁾, a bounding box unification technique catering to close-by objects. Experiments with the publicly available KITTI⁴⁾ data acquired from vehicle mounted camera proved the effectiveness of the proposed method.