Abstract
This paper presents a pedestrian detection framework using a top-view camera. The paper contains two novel contributions for the pedestrian detection task: 1. Using shape context method to estimate the pedestrian directions and normalizing the pedestrian regions. 2. Based on the locations of the extracted head candidates, system chooses the most adaptive classifier from several classifiers automatically. Our proposed methods may solve the difficulties on top-view pedestrian detection field. Experimental was performed on video sequences with different illumination and crowed conditions, the experimental results demonstrate the efficiency of our algorithm. Copyright © 2011 The Institute of Electronics, Information and Communication Engineers.
| Original language | English |
|---|---|
| Pages (from-to) | 1269-1277 |
| Number of pages | 9 |
| Journal | IEICE Transactions on Information and Systems |
| Volume | E94-D |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 1 Jun 2011 |
| Externally published | Yes |
Bibliographical note
This work is supported in part by Program for Changjiang Scholars and Innovative Research Team in University under Grant No.IRT0949.Keywords
- Pedestrian detection
- People counting
- Top-view camera