Name
Title | ||
|---|---|---|
Fast human detection in crowded scenes by contour integration and local shape estimation |
Abstract | ||
|---|---|---|
The complexity of human detection increases significantly with a growing density of humans populating a scene. This paper presents a Bayesian detection framework using shape and motion cues to obtain a maximum a posteriori (MAP) solution for human configurations consisting of many, possibly occluded pedestrians viewed by a stationary camera. The paper contains two novel contributions for the human detection task: 1. computationally efficient detection based on shape templates using contour integration by means of integral images which are built by oriented string scans; (2) a non-parametric approach using an approximated version of the Shape Context descriptor which generates informative object parts and infers the presence of humans despite occlusions. The outputs of the two detectors are used to generate a spatial configuration of hypothesized human body locations. The configuration is iteratively optimized while taking into account the depth ordering and occlusion status of the hypotheses. The method achieves fast computation times even in complex scenarios with a high density of people. Its validity is demonstrated on a substantial amount of image data using the CAVIAR and our own datasets. Evaluation results and comparison with state of the art are presented. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CVPRW.2009.5206564 | CVPR |
Keywords | Field | DocType |
Bayes methods,edge detection,image motion analysis,maximum likelihood estimation,object detection,Bayesian detection framework,CAVIAR,contour integration,crowded scenes,fast human detection,integral images,local shape estimation,maximum a posteriori solution,motion cues,nonparametric approach,oriented string scans,shape context descriptor,shape templates | Computer vision,Object detection,Pattern recognition,Computer science,Edge detection,Methods of contour integration,Image segmentation,Artificial intelligence,Pixel,Maximum a posteriori estimation,Shape context,Computation | Conference |
Volume | Issue | ISSN |
2009 | 1 | 1063-6919 |
Citations | PageRank | References |
27 | 1.02 | 19 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Csaba Beleznai | 1 | 367 | 18.96 |
| Horst Bischof | 2 | 8751 | 541.43 |