基于结构化约束的多视角人体检测方法

Multi-View Body Structure-Constrainted Human Detection Method

针对单视角下信息量不足以及多视角不同视角间信息关联困难的问题,提出了基于结构化约束的多视角人体检测方法.首先通过基于块的人体检测模型获取人体局部块信息;然后采用空间仿射变换将不同视角下重叠区域通过变换矩阵的映射关系关联起来;最后针对仿射变换后的区域因遮挡或者存在多目标导致多视角目标关联困难的问题,利用人体局部显著块间的结构化约束为多视角目标匹配构造最大后验概率模型,通过最优求解获取多视角目标匹配结果.实验结果表明,该方法能够利用多视角信息来有效弥补单视角下人体检测中出现的遮挡问题,显著提高了人体检测效果.

To solve the problems of lack of information in single-view and the difficulty in information correspon-dence in different views,a multi-view body structure-constrainted human detection method was proposed. First, part-based human detection model is implemented to obtain the information on human body part. Then leverage spatial affine transform to correlate the overlapping regions in different views. Finally,to overcome the challenge of object corresponding in multi-view environment caused by partial occlusion and multiple target existence in neighborhood, the model of maximum a posterior（MAP）isdeveloped for multi-view object matching by taking advantage of the body structure constraints. The multi-view object matching result can be achieved by optimizing the objective function of the modal.The experimental results show that the proposed method can improve human detection by efficiently using multi-view cues to avoid partial occlusion in single-view.