Projected Texture for Object Classification

Algorithms for classification of 3D objects either recover the depth information lost during imaging using multiple images, structured lighting, image cues, etc. or work directly the images for classification. While the latter class of algorithms are more efficient and robust in comparison, they are less accurate due to the lack of depth information. We propose the use of structured lighting patterns projected on the object, which gets deformed according to the shape of the object. Since our goal is object classification and not shape recovery, we characterize the deformations using simple texture measures, thus avoiding the error prone and computationally expensive step of depth recovery. Moreover, since the deformations encode depth variations of the object, the 3D shape information is implicitly used for classification. We show that the information thus derived can significantly improve the accuracy of object classification algorithms, and derive the theoretical limits on height var...

• Type: Conference
• Year: 2008
• Where: ECCV
• Authors: Avinash Sharma, Anoop M. Namboodiri
• Keywords: Computer Vision, Depth Variations, ECCV 2008, Equal Error Rate, Object Classification Algorithms, Structured Lighting Patterns, Texture Classification Algorithm