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|
|Number of pages||8|
|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
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009|
|Period||9/2/09 → 9/4/09|
Bibliographical noteFunding Information:
This work has been supported in part by the European Commission Seventh Framework Programme Marie Curie International Reintegration Grant IRG-239494.
- Optic flow
- Reflectance classification
- Rigidity detection
- Specular motion