Rapid inference of object rigidity and reflectance using optic flow

Di Zang; Katja Doerschner; Paul R Schrater

doi:10.1007/978-3-642-03767-2_107

Rapid inference of object rigidity and reflectance using optic flow

Di Zang, Katja Doerschner, Paul R Schrater

Psychology (Twin Cities)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

Rigidity and reflectance are key object properties, important in their own rights, and they are key properties that stratify motion reconstruction algorithms. However, the inference of rigidity and reflectance are both difficult without additional information about the object's shape, the environment, or lighting. For humans, relative motions of object and observer provides rich information about object shape, rigidity, and reflectivity. We show that it is possible to detect rigid object motion for both specular and diffuse reflective surfaces using only optic flow, and that flow can distinguish specular and diffuse motion for rigid objects. Unlike nonrigid objects, optic flow fields for rigid moving surfaces are constrained by a global transformation, which can be detected using an optic flow matching procedure across time. In addition, using a Procrustes analysis of structure from motion reconstructed 3D points, we show how to classify specular from diffuse surfaces.

Original language	English (US)
Title of host publication	Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings
Pages	881-888
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-03767-2_107
State	Published - 2009
Event	13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009 - Munster, Germany Duration: Sep 2 2009 → Sep 4 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5702 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009
Country/Territory	Germany
City	Munster
Period	9/2/09 → 9/4/09

Bibliographical note

Funding Information:
This work has been supported in part by the European Commission Seventh Framework Programme Marie Curie International Reintegration Grant IRG-239494.

Keywords

Optic flow
Reflectance classification
Rigidity detection
Specular motion

Publisher link

10.1007/978-3-642-03767-2_107

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Zang, D., Doerschner, K., & Schrater, P. R. (2009). Rapid inference of object rigidity and reflectance using optic flow. In Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings (pp. 881-888). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5702 LNCS). https://doi.org/10.1007/978-3-642-03767-2_107

Rapid inference of object rigidity and reflectance using optic flow. / Zang, Di; Doerschner, Katja; Schrater, Paul R.
Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings. 2009. p. 881-888 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5702 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zang, D, Doerschner, K & Schrater, PR 2009, Rapid inference of object rigidity and reflectance using optic flow. in Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5702 LNCS, pp. 881-888, 13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009, Munster, Germany, 9/2/09. https://doi.org/10.1007/978-3-642-03767-2_107

Zang D, Doerschner K, Schrater PR. Rapid inference of object rigidity and reflectance using optic flow. In Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings. 2009. p. 881-888. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-03767-2_107

Zang, Di ; Doerschner, Katja ; Schrater, Paul R. / Rapid inference of object rigidity and reflectance using optic flow. Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings. 2009. pp. 881-888 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Rapid inference of object rigidity and reflectance using optic flow",

abstract = "Rigidity and reflectance are key object properties, important in their own rights, and they are key properties that stratify motion reconstruction algorithms. However, the inference of rigidity and reflectance are both difficult without additional information about the object's shape, the environment, or lighting. For humans, relative motions of object and observer provides rich information about object shape, rigidity, and reflectivity. We show that it is possible to detect rigid object motion for both specular and diffuse reflective surfaces using only optic flow, and that flow can distinguish specular and diffuse motion for rigid objects. Unlike nonrigid objects, optic flow fields for rigid moving surfaces are constrained by a global transformation, which can be detected using an optic flow matching procedure across time. In addition, using a Procrustes analysis of structure from motion reconstructed 3D points, we show how to classify specular from diffuse surfaces.",

keywords = "Optic flow, Reflectance classification, Rigidity detection, Specular motion",

author = "Di Zang and Katja Doerschner and Schrater, {Paul R}",

note = "Funding Information: This work has been supported in part by the European Commission Seventh Framework Programme Marie Curie International Reintegration Grant IRG-239494.; 13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009 ; Conference date: 02-09-2009 Through 04-09-2009",

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N2 - Rigidity and reflectance are key object properties, important in their own rights, and they are key properties that stratify motion reconstruction algorithms. However, the inference of rigidity and reflectance are both difficult without additional information about the object's shape, the environment, or lighting. For humans, relative motions of object and observer provides rich information about object shape, rigidity, and reflectivity. We show that it is possible to detect rigid object motion for both specular and diffuse reflective surfaces using only optic flow, and that flow can distinguish specular and diffuse motion for rigid objects. Unlike nonrigid objects, optic flow fields for rigid moving surfaces are constrained by a global transformation, which can be detected using an optic flow matching procedure across time. In addition, using a Procrustes analysis of structure from motion reconstructed 3D points, we show how to classify specular from diffuse surfaces.

AB - Rigidity and reflectance are key object properties, important in their own rights, and they are key properties that stratify motion reconstruction algorithms. However, the inference of rigidity and reflectance are both difficult without additional information about the object's shape, the environment, or lighting. For humans, relative motions of object and observer provides rich information about object shape, rigidity, and reflectivity. We show that it is possible to detect rigid object motion for both specular and diffuse reflective surfaces using only optic flow, and that flow can distinguish specular and diffuse motion for rigid objects. Unlike nonrigid objects, optic flow fields for rigid moving surfaces are constrained by a global transformation, which can be detected using an optic flow matching procedure across time. In addition, using a Procrustes analysis of structure from motion reconstructed 3D points, we show how to classify specular from diffuse surfaces.

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Rapid inference of object rigidity and reflectance using optic flow

Abstract

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Keywords

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