Augmenting cartographic resources for autonomous driving
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Self-supervised aerial image analysis for extracting parking lot structure
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A new level-set based algorithm for bimodal depth segmentation
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
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This paper presents unsupervised vision-based system for parking lot occupancy detection. The proposed method exhibit low computation complexity and use just a few frames per minute. Method is based on three main processing stages. In the first section, raw image acquired by camera system is preprocessed. Shadows in the image are significantly attenuated or completely removed. The image distortion is corrected subsequently. In the following step optimal correspondences between one or more stationary cameras and visible parking places are established. During this process occlusions are taken in account. Finally, a parking place status is evaluated. Acquired information about parking lot occupancy can be served to another system, e.g. intelligent transportation system. Experimental results from both artificial and real scenes show promising results even on quite challenging conditions. Nonetheless a scope for improvement of presented method is given.