Title :
Estimating 3D motion and shape of multiple objects using Hough transform
Author :
Tian, Tina Yu ; Shah, Mubarak
Author_Institution :
Dept. of Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
Abstract :
Presents a robust method to determine 3D motion and structure of multiple objects. Rather than segmenting the scene containing multiple motions using 3D parametric model, the authors use the general 3D motion model and exploit Hough transform and robust estimation techniques to determine motion and segmentation simultaneously for an arbitrary scene. The authors divide the input image into patches, and for each sample of the translation space and each patch, the authors compute the rotation parameters using weighted least-squares fit. Each patch votes for a sample in the five-dimensional parameter space (translation and rotation). The multiple local maxima in the parameter space naturally correspond to the multiple moving objects. The authors´ experimental results show that the proposed method is robust and relatively insensitive to noise
Keywords :
motion estimation; 3D motion estimation; Hough transform; five-dimensional parameter space; multiple objects; robust estimation techniques; rotation; segmentation; shape estimation; translation; weighted least-squares fit; Computer vision; Image motion analysis; Image segmentation; Layout; Motion estimation; Noise robustness; Optical computing; Optical noise; Parametric statistics; Shape;
Conference_Titel :
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6265-4
DOI :
10.1109/ICPR.1994.576390