3D keypoint detectors and descriptors for 3D objects recognition with TOF camera

Ayet Shaiek; Fabien Moutarde

doi:10.1117/12.872483

27 January 2011 3D keypoint detectors and descriptors for 3D objects recognition with TOF camera

Ayet Shaiek, Fabien Moutarde

Proceedings Volume 7864, Three-Dimensional Imaging, Interaction, and Measurement; 78640Q (2011) https://doi.org/10.1117/12.872483
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

The goal of this work is to evaluate 3D keypoints detectors and descriptors, which could be used for quasi real time 3D object recognition. The work presented has three main objectives: extracting descriptors from real depth images, obtaining an accurate degree of invariance and robustness to scale and viewpoints, and maintaining the computation time as low as possible. Using a 3D time-of-flight (ToF) depth camera, we record a sequence for several objects at 3 different distances and from 5 viewpoints. 3D salient points are then extracted using 2 different curvatures-based detectors. For each point, two local surface descriptors are computed by combining the shape index histogram and the normalized histogram of angles between the normal of reference feature point and the normals of its neighbours. A comparison of the two detectors and descriptors was conducted on 4 different objects. Experimentations show that both detectors and descriptors are rather invariant to variations of scale and viewpoint. We also find that the new 3D keypoints detector proposed by us is more stable than a previously proposed Shape Index based detector.

Citation Download Citation

Ayet Shaiek and Fabien Moutarde "3D keypoint detectors and descriptors for 3D objects recognition with TOF camera", Proc. SPIE 7864, Three-Dimensional Imaging, Interaction, and Measurement, 78640Q (27 January 2011); https://doi.org/10.1117/12.872483

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KEYWORDS

Sensors

3D-TOF imaging

Object recognition

3D image processing

Time of flight cameras

Cameras

3D modeling

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