Human Body Detection by Using the Parts Probabilities Connection Network

Abstract

We propose a method of human body detection and pose estimation from a complex image by using the simple feature extraction. We extract the elliptic shapes as head candidates and parallel lines as arms ans legs candidates from the image. Next the likelihoods of each body part are calculated for each candidates. The total likelihood of entire body is computed by combining them with knowledges about the connection of the positions between body parts. We construct the Parts Probabilities Connection Network, and optimize it by using the genetic algorithm. We report the experimental result to show the effectiveness of the proposed method.