Toward Augmenting Everything: Detecting and Tracking Geometrical Features on Planar Objects

H. Uchiyama 1 E. Marchand 1
1 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 : This paper presents an approach for detecting and tracking various types of planar objects with geometrical features. We combine tra- ditional keypoint detectors with Locally Likely Arrangement Hash- ing (LLAH) 21 for geometrical feature based keypoint matching. Because the stability of keypoint extraction affects the accuracy of the keypoint matching, we set the criteria of keypoint selection on keypoint response and the distance between keypoints. In order to produce robustness to scale changes, we build a non-uniform im- age pyramid according to keypoint distribution at each scale. In the experiments, we evaluate the applicability of traditional keypoint detectors with LLAH for the detection. We also compare our ap- proach with SURF and finally demonstrate that it is possible to de- tect and track different types of textures including colorful pictures, binary fiducial markers and handwritings.
Keywords : Augmented Reality
Type de document :
Communication dans un congrès
IEEE Int. Symp. on Mixed and Augmented Reality, ISMAR'11, 2011, Basel, Switzeland, Switzerland. pp.17-25, 2011
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H. Uchiyama, E. Marchand. Toward Augmenting Everything: Detecting and Tracking Geometrical Features on Planar Objects. IEEE Int. Symp. on Mixed and Augmented Reality, ISMAR'11, 2011, Basel, Switzeland, Switzerland. pp.17-25, 2011. 〈hal-00639704〉

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