Keypoint detection in RGBD images based on an efficient viewpoint-covariant multiscale representationReportar como inadecuado




Keypoint detection in RGBD images based on an efficient viewpoint-covariant multiscale representation - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1 LTCI - Laboratoire Traitement et Communication de l-Information 2 TSI - Département Traitement du Signal et des Images

Abstract : Texture+depth RGBD images provide information about the geometry of a scene, which could help improve current image matching performance, e.g., in presence of large viewpoint changes. While depth has been mainly used for processing keypoint descriptors, in this paper we focus on the keypoint detection problem. In order to produce a computationally efficient viewpoint-covariant multiscale representation, we design an image smoothing procedure which locally smooths a texture image based on the corresponding depth. This yields an approximated scale space, where we can find keypoints using a multiscale detector approach. Our experiments on both synthetic and real-world images show substantial gains with respect to 2D and other RGBD feature extraction approaches.

Keywords : RGBD texture+depth scale space keypoint detection visual odometry





Autor: Maxim Karpushin - Giuseppe Valenzise - Frédéric Dufaux -

Fuente: https://hal.archives-ouvertes.fr/



DESCARGAR PDF




Documentos relacionados