A hybrid Hough-Hausdorff method for recognizing bicycles in natural scenes

This paper presents research on a new computer vision approach to an intelligent transportation system domain: bicycle counting. Traditionally, bicycles have not received the attention of transportation departments for a variety of reasons. As a result, effective and portable automatic methods for counting bicycles have not been developed. This paper presents a method for identifying bicycles in natural scenes taken from either time-lapse or full-motion video streams. The method is based on a blend of two separate techniques, the Hough transform and the directed Hausdorff distance. Experimental results demonstrate that neither technique individually achieves the performance of the hybrid technique.

[1]  Christopher M. Brown.  Inherent Bias and Noise in the Hough Transform , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Daniel P. Huttenlocher,et al.  A multi-resolution technique for comparing images using the Hausdorff distance , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[3]  William Rucklidge,et al.  Locating objects using the Hausdorff distance , 1995, Proceedings of IEEE International Conference on Computer Vision.

[4]  Nikolaos Papanikolopoulos,et al.  A ROBUST VIDEO-BASED BICYCLE COUNTING SYSTEM , 1999 .

[5]  Daniel P. Huttenlocher,et al.  Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  William Rucklidge.  Lower Bounds for the Complexity of the Hausdorff Distance , 1993, CCCG.

[7]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[8]  Mikhail J. Atallah,et al.  A Linear Time Algorithm for the Hausdorff Distance Between Convex Polygons , 1983, Inf. Process. Lett..

[9]  Daniel P. Huttenlocher,et al.  Computing the minimum Hausdorff distance for point sets under translation , 1990, SCG '90.

[10]  David G. Stork,et al.  Pattern Classification , 1973 .