Title :
A variable window approach to early vision
Author :
Boykov, Yuri ; Veksler, Olga ; Zabih, Ramin
Author_Institution :
Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA
fDate :
12/1/1998 12:00:00 AM
Abstract :
Early vision relies heavily on rectangular windows for tasks such as smoothing and computing correspondence. While rectangular windows are efficient, they yield poor results near object boundaries. We describe an efficient method for choosing an arbitrarily shaped connected window, in a manner that varies at each pixel. Our approach can be applied to several problems, including image restoration and visual correspondence. It runs in linear time, and takes a few seconds on traditional benchmark images. Performance on both synthetic and real imagery appears promising
Keywords :
computer vision; image restoration; motion estimation; stereo image processing; adaptive window; early vision; image restoration; motion estimation; stereo image analysis; variable window; visual correspondence; Aggregates; Computer vision; Image restoration; Least squares methods; Motion estimation; Noise shaping; Shape; Smoothing methods; Statistics;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on