Lima12b

J.P. Lima, V. Teichrieb, H.and Marchand, E. Uchiyama. Object Detection and Pose Estimation from Natural Features Using Consumer RGB-D Sensors: Applications in Augmented Reality. In IEEE Int. Symp. on Mixed and Augmented Reality (doctoral symposium), ISMAR'12, Atlanta, USA, November 2012.

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Abstract

The work proposed in this document aims to investigate the use of consumer RGB-D sensors for object detection and pose estimation from natural features, with the purpose of using such techniques for developing augmented reality applications. Two methods based on depth-assisted rectification are proposed, which transform features extracted from the color image to a canonical view using depth data in order to obtain a representation invariant to rotation, scale and perspective distortions. While one method is suitable for textured objects, either planar or non-planar, the other method focuses on texture-less planar objects. Qualitative and quantitative evaluations of the proposed methods are performed, comparing it to existing methods for object detection and pose estimation

BibTex Reference

@InProceedings{Lima12b,
   Author = {Lima, J.P. and Teichrieb, V. and Uchiyama, H.and Marchand, E.},
   Title = {Object Detection and Pose Estimation from Natural Features Using Consumer RGB-D Sensors: Applications in Augmented Reality},
   BookTitle = {IEEE Int. Symp. on Mixed and Augmented Reality (doctoral symposium), ISMAR'12},
   Address = {Atlanta, USA},
   Month = {November},
   Year = {2012}
}

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