Study on motion estimation using local minima

Min-Sup Lee; Shiryong Yu

doi:10.1117/12.161467

4 November 1993 Study on motion estimation using local minima

Min-Sup Lee, Shiryong Yu

Proceedings Volume 1976, High-Definition Video; (1993) https://doi.org/10.1117/12.161467
Event: Video Communications and Fiber Optic Networks, 1993, Berlin, Germany

Abstract

Block matching algorithm has been widely employed in motion estimation, because of its simplicity of implementation. Among them the full search algorithm gives the optimal solution within the search area except the exhaustive computational cost. On the contrary, other fast search algorithms have the shortcomings of finding the local minimum due to coarse sampling positions. In this paper two issues, speed and local minimum, are dramatically improved by using the line projection and local minima. The proposed algorithm is constructed of two stages. First some candidates, local minima, for global minimum are selected by using the full search on the line projection data. And then these candidates are checked by general block matching algorithm. The performance of the proposed algorithm approaches that of the full search algorithm, but the computational cost is much less than the full search algorithm.

Citation Download Citation

Min-Sup Lee and Shiryong Yu "Study on motion estimation using local minima", Proc. SPIE 1976, High-Definition Video, (4 November 1993); https://doi.org/10.1117/12.161467

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available