A Nighttime Part-based Cyclist Detection System Using Spatial and Appearance Information
Date Issued
2014
Date
2014
Author(s)
Chen, Yi-Hsiang
Abstract
Obstacle on road detection is an important issue in the field of intelligent transportation system. The research of pedestrian detection attracts attention due to the weakness of feature and descriptor. Some other obstacles, such as the cyclists, having weaker descriptive features are seldom discussed. The cyclist, of course, is not a light source and there are seldom or even no light source fixed on the two-wheel vehicles. Hence, it is notable to build a nighttime cyclist detection system to assist the vehicle driver. Thus, in this thesis, we propose a cyclist detection method for a moving vehicle equipped with a near-infrared camera. It will increase the difficulty when the detected objects including two-wheel vehicles due to some inherent properties of the two-wheel vehicles. For example, the aspect ratio varies depending on different viewpoints. Namely, the occlusion effect between cyclist and two-wheel vehicle varies with the viewpoint. To solve this problem, we employ the part-based object detection in this thesis as the main stream solution approach. Moreover, we use two kinds of additional information to verify the part-based detection result. The first one is the obvious contour appearance of two-wheel vehicle and its interior spatial relation with high stability. The second is the primary characteristic of the NIR image. Finally, experiments show that our system is verified and demonstrated in a nice performance.
Subjects
物體偵測
夜間
近紅外線
幾何資訊
空間關係
方向梯度直方圖
Type
thesis
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