This paper discusses the pedestrian counting method in video sequences gathered from a fixed camera.According to the profile characteristic and color feather of a person's head,this paper proposes a novel algorithm which can be better used for sparse crowd to detect head.Then the central point of the head area is regarded as the feature point of a pedestrian.With the points,a match algorithm based on object motion continuity is used for head matching and tracking to implements a whole system for crowd counting.Large numbers of experimental results on several real video sequences demonstrates real-time effect and the high precision for various environments.

Pedestrian Count Method Based on Head Feature

Analyzing object recognition in complicated traffic environment with principle of point distribution in multi-dimensional space and Biomimetic Pattern Recognition, a novel algorithm of automatic threshold for head recognition is proposed basing on multi-weight and triangle covering Getting the initial head samples from head detection of the looked-down video stream, extracting features of these samples and mapping them into multi-dimensional feature space, then obtaining the density-threshold radius according to the distribution density of head samples automatically to cover all the heads with triangle, lastly further dividing the samples that are overlapping covered in order to discriminate the head images Results of experiment in UCI database and video data of head show that the method is valid and efficient

Jiafu Jiang

Papers

Notice of Retraction Study of head recognition based on biomimetic pattern recognition in complicated traffic environment