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Motion-Model-Based Boundary Extraction

Published

Author(s)

H Liu, Tsai H. Hong, Martin Herman, Rama Chellappa

Abstract

Motion boundary extraction and optical flow computation are two subproblems of the motion recovery problem that cannot be solved independently of each other. They represent the most common dilemma in motion research. A popular approach uses an iterative scheme that consists of motion boundary extraction and optical flow computation components and refines each result through iteration. This approach is typically timeconsuming and sometimes does not converge. We present a local, noniterative algorithm that extracts motion boundaries and computes optical flow simultaneously. This is achieved by modeling a 3-D image intensity block with a general motion model that presumes locally coherent motion. Local motion coherence, which is measured by the fitness of the motion model, is the criterion we use to determine whether motion should be estimated, or otherwise motion boundaries should be located. The motion boundary extraction algorithm is evaluated quantitatively and qualitatively against other existing algorithms in a scheme originally developed for edge detection. The results show that our algorithm is accurate in locating boundaries. The flow portion of the algorithm is presented in another paper[24] .
Citation
NIST Interagency/Internal Report (NISTIR) - 5587
Report Number
5587

Keywords

Mobility, Vision, motion analysis, segmentation

Citation

Liu, H. , Hong, T. , Herman, M. and Chellappa, R. (1995), Motion-Model-Based Boundary Extraction, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=820517 (Accessed February 25, 2024)
Created December 31, 1994, Updated October 12, 2021