A graphics hardware implementation of the generalized Hough transform for fast object recognition, scale, and 3D pose detection

The generalized Hough transform constitutes a wellknown approach to object recognition and pose detection. To attain reliable detection results, however, a very large number of candidate object poses and scale factors need to be considered. In this paper we employ an inexpensive, consumer-market graphics card as the “poor man’s” parallel processing system. We describe the implementation of a fast and enhanced version of the generalized Hough transform on graphics hardware. Thanks to the high bandwidth of on-board texture memory, a single pose can be evaluated in less than 3 ms, independent of the number of edge pixels in the image. From known object geometry, our hardwareaccelerated generalized Hough transform algorithm is capable of detecting an object’s 3D pose, scale, and position in the image within less than one minute. A good pose estimation is delivered in even less than 10 seconds.