Object Detection and Pose Estimation from Natural Features Using Consumer RGB-D Sensors: Applications in Augmented Reality

João Paulo Lima 1 Veronica Teichrieb 1 Hideaki Uchiyama 2 Eric Marchand 2
2 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
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.
Type de document :
Communication dans un congrès
IEEE Int. Symp. on Mixed and Augmented Reality (doctoral symposium), ISMAR'12, 2012, Atlanta, United States. 2012
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Dernière modification le : mardi 16 janvier 2018 - 15:54:11
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João Paulo Lima, Veronica Teichrieb, Hideaki Uchiyama, Eric Marchand. Object Detection and Pose Estimation from Natural Features Using Consumer RGB-D Sensors: Applications in Augmented Reality. IEEE Int. Symp. on Mixed and Augmented Reality (doctoral symposium), ISMAR'12, 2012, Atlanta, United States. 2012. 〈hal-00750617〉

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