Training Physical and Geometrical Mid-Points for Multi-person Pose Estimation and Human Detection Under Congestion and Low Resolution

This paper introduces the design and evaluation of NeoPose which is developed for multi-person pose estimation and human detection. The design of NeoPose is targeting the issue of human detection under congested situation and with low resolution in the image. Under such situations, we compared the performance of different versions of NeoPose as well as other existing algorithms in a human detection task. Throughout the task, the usefulness of two kinds of mid-point (physical and geometrical mid-points) and a deconvolution structure was discussed. Experiment results indicated that NeoPose which applied geometrical mid-points and deconvolution structure performed the best in terms of both precision and recall in the evaluation.