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Conference Papers Year : 2012

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

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.
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Dates and versions

hal-00750617 , version 1 (11-11-2012)

Identifiers

  • HAL Id : hal-00750617 , version 1

Cite

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. ⟨hal-00750617⟩
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