On Refractive Optical Flow

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

On Refractive Optical Flow. / Agarwal, Sameer; Mallick, Satya P.; Kriegman, David; Belongie, Serge.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2004, p. 483-494.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Agarwal, S, Mallick, SP, Kriegman, D & Belongie, S 2004, 'On Refractive Optical Flow', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 483-494. https://doi.org/10.1007/978-3-540-24671-8_38

APA

Agarwal, S., Mallick, S. P., Kriegman, D., & Belongie, S. (2004). On Refractive Optical Flow. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 483-494. https://doi.org/10.1007/978-3-540-24671-8_38

Vancouver

Agarwal S, Mallick SP, Kriegman D, Belongie S. On Refractive Optical Flow. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2004;483-494. https://doi.org/10.1007/978-3-540-24671-8_38

Author

Agarwal, Sameer ; Mallick, Satya P. ; Kriegman, David ; Belongie, Serge. / On Refractive Optical Flow. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2004 ; pp. 483-494.

Bibtex

@article{ed513da8f9174e06ae52c2e779828f00,
title = "On Refractive Optical Flow",
abstract = "This paper presents a novel generalization of the optical flow equation to the case of refraction, and it describes a method for recovering the refractive structure of an object from a video sequence acquired as the background behind the refracting object moves. By structure here we mean a representation of how the object warps and attenuates (or amplifies) the light passing through it. We distinguish between the cases when the background motion is known and unknown. We show that when the motion is unknown, the refractive structure can only be estimated up to a six-parameter family of solutions without additional sources of information. Methods for solving for the refractive structure are described in both cases. The performance of the algorithm is demonstrated on real data, and results of applying the estimated refractive structure to the task of environment matting and compositing are presented.",
author = "Sameer Agarwal and Mallick, {Satya P.} and David Kriegman and Serge Belongie",
year = "2004",
doi = "10.1007/978-3-540-24671-8_38",
language = "English",
pages = "483--494",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",
publisher = "Springer Verlag",

}

RIS

TY - JOUR

T1 - On Refractive Optical Flow

AU - Agarwal, Sameer

AU - Mallick, Satya P.

AU - Kriegman, David

AU - Belongie, Serge

PY - 2004

Y1 - 2004

N2 - This paper presents a novel generalization of the optical flow equation to the case of refraction, and it describes a method for recovering the refractive structure of an object from a video sequence acquired as the background behind the refracting object moves. By structure here we mean a representation of how the object warps and attenuates (or amplifies) the light passing through it. We distinguish between the cases when the background motion is known and unknown. We show that when the motion is unknown, the refractive structure can only be estimated up to a six-parameter family of solutions without additional sources of information. Methods for solving for the refractive structure are described in both cases. The performance of the algorithm is demonstrated on real data, and results of applying the estimated refractive structure to the task of environment matting and compositing are presented.

AB - This paper presents a novel generalization of the optical flow equation to the case of refraction, and it describes a method for recovering the refractive structure of an object from a video sequence acquired as the background behind the refracting object moves. By structure here we mean a representation of how the object warps and attenuates (or amplifies) the light passing through it. We distinguish between the cases when the background motion is known and unknown. We show that when the motion is unknown, the refractive structure can only be estimated up to a six-parameter family of solutions without additional sources of information. Methods for solving for the refractive structure are described in both cases. The performance of the algorithm is demonstrated on real data, and results of applying the estimated refractive structure to the task of environment matting and compositing are presented.

UR - http://www.scopus.com/inward/record.url?scp=24644496412&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-24671-8_38

DO - 10.1007/978-3-540-24671-8_38

M3 - Journal article

AN - SCOPUS:24644496412

SP - 483

EP - 494

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

ER -

ID: 302055663