Perspective invariant movie analysis for depth recovery

Lionel Moisan

doi:10.1117/12.218489

1 September 1995 Perspective invariant movie analysis for depth recovery

Lionel Moisan

Proceedings Volume 2567, Investigative and Trial Image Processing; (1995) https://doi.org/10.1117/12.218489
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

Processing entire movies and taking advantage of the interframe redundancy is the key of shape-from-motion analysis. Thus, recovering the depth of a fixed scene from an image sequence can be viewed as a movie processing problem: how to focus the redundant depth information of a noisy image sequence into a perfect depth-coherent movie? We present a natural set of axioms in agreement with the depth recovery, in the simple case of a straight movement of the camera parallel to the focal plane. According to these axioms, we show that there is a unique depth-coherent way of processing movies, described by a nonlinear partial differential equation. The corresponding multiscale analysis has the property of smoothing the motion field of a movie, leading naturally to a perfect motion field compatible with a depth interpretation. Moreover, in the case of an ideal movie, i.e. coherent with the observation of a fixed 3D scene, this analysis can be viewed as a simple filtering of the camera movement preserving the depth interpretation given by the movie, and is thereby perspective invariant. Last, we study a numerical scheme, compatible with the theoretical axioms, and produce some experiments on synthetic noisy movies.

Citation Download Citation

Lionel Moisan "Perspective invariant movie analysis for depth recovery", Proc. SPIE 2567, Investigative and Trial Image Processing, (1 September 1995); https://doi.org/10.1117/12.218489

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