Edges detection in depth images for a gesture recognition application using a Kinect WSN

Asma Ben Hadj Mohamed (1) , Amal Baghdadi (1) , Thierry Val (1, 2) , Laurent Andrieux (1) , Abdennaceur Kachouri (3)

1 IRIT-RMESS - Réseaux, Mobiles, Embarqués, Sans fil, Satellites
2 UT2J - Université Toulouse - Jean Jaurès
3 CEM Lab - ENIS - Département de Génie Électrique de Sfax [ENIS]

The detection of persons in an image has been the subject of several studies. Most of these works were done on images taken by cameras in visible light (RGB). In this paper, we are interested in people contours detection on the Kinect 3D images. We investigate the application of Gradient approach and optimal filters on depth images. We also use this detection to monitor the person via her gestures. Results show that edge detection of Canny is good for people in both light condition but, the performance of Sobel algorithm was better for the images taken in the dark depths.

Mots clés: Kinect; Gestures recognition; People edge detection; Depth images; 3D images

Domaines: Réseaux et télécommunications [cs.NI]; Système d'exploitation [cs.OS]; Architectures Matérielles [cs.AR]; Systèmes embarqués

Asma Ben Hadj Mohamed, Amal Baghdadi, Thierry Val, Laurent Andrieux, Abdennaceur Kachouri. Edges detection in depth images for a gesture recognition application using a Kinect WSN. 5th International Conference on Web and Information Technologies (ICWIT 2013), May 2013, Hammamet, Tunisia. pp. 1-10. ⟨hal-01240707⟩