標題: Vacant Parking Space Detection Based on Plane-based Bayesian Hierarchical Framework
作者: Huang, Ching-Chun
Tai, Yu-Shu
Wang, Sheng-Jyh
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
關鍵字: Bayesian inference;histogram of oriented gradients;image classification;parking space detection
公開日期: 1-九月-2013
摘要: In this paper, we propose a vacant parking space detection system that operates day and night. In the daytime, the major challenges of the system include dramatic lighting variations, shadow effect, inter-object occlusion, and perspective distortion. In the nighttime, the major challenges include insufficient illumination and complicated lighting conditions. To overcome these problems, we propose a plane-based method which adopts a structural 3-D parking lot model consisting of plentiful planar surfaces. The plane-based 3-D scene model plays a key part in handling inter-object occlusion and perspective distortion. On the other hand, to alleviate the interference of unpredictable lighting changes and shadows, we propose a plane-based classification process. Moreover, by introducing a Bayesian hierarchical framework to integrate the 3-D model with the plane-based classification process, we systematically infer the parking status. Last, to overcome the insufficient illumination in the nighttime, we also introduce a preprocessing step to enhance image quality. The experimental results show that the proposed framework can achieve robust detection of vacant parking spaces in both daytime and nighttime.
URI: http://dx.doi.org/10.1109/TCSVT.2013.2254961
http://hdl.handle.net/11536/22777
ISSN: 1051-8215
DOI: 10.1109/TCSVT.2013.2254961
期刊: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
Volume: 23
Issue: 9
起始頁: 1598
結束頁: 1610
顯示於類別:期刊論文


文件中的檔案:

  1. 000324254500013.pdf