https://scholars.lib.ntu.edu.tw/handle/123456789/489039
Title: | Near-infrared based nighttime pedestrian detection by combining multiple features. | Authors: | Lin, Yu-Chun Chan, Yi-Ming Chuang, Luo-Chieh LI-CHEN FU Huang, Shih-Shinh Hsiao, Pei-Yung Luo, Min-Fang |
Keywords: | Contour; Detection; HOG; Human; Nighttime; Pedestrian; SVM | Issue Date: | 2011 | Start page/Pages: | 1549-1554 | Source: | IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC | Conference: | 14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011 | Abstract: | Pedestrian detection is important in the computer vision field. In the nighttime, pedestrian detection is even more valuable. In this paper, we address the issue of detecting pedestrians in video streams from a moving camera at nighttime. Most nighttime human detection approaches only use single feature extracted from images. The effective image features in daytime environment may suffer from textureless, high contrast and low light problems at night. To deal with these issues, we first segment the foreground by using the proposed Smart Region Detection approach to generate candidates. Then we design a nighttime pedestrian detection system based on the AdaBoost and the support vector machine (SVM) classifiers with contour and histogram of oriented gradients (HOG) features to effectively recognize pedestrians from those candidates. Combining different type of complementary features improve the detection performance. Results show that our pedestrian detection system is promising in the nighttime environment. © 2011 IEEE. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/489039 https://www.scopus.com/inward/record.uri?eid=2-s2.0-83755228815&doi=10.1109%2fITSC.2011.6083015&partnerID=40&md5=57451582945c601007b4274fb49ede68 |
DOI: | 10.1109/ITSC.2011.6083015 | SDG/Keyword: | Contour; HOG; Human; Nighttime; Pedestrian; SVM; Adaptive boosting; Computer vision; Error detection; Feature extraction; Intelligent systems; Support vector machines |
Appears in Collections: | 資訊工程學系 |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.