Hye-mi Kim

Face Recognition using 3D Line Edge Map Robust to Expression Changes and Occlusions

We propose new face recognition algorithm using 3D line edge map as combining 3D information on the edge obtained by stereo camera and the conventional line edge map algorithm. As a similarity measure of 3D line edge map, weighted partial and spatially well-localized line segment Hausdorff distance (WPSLHD) is proposed. WPSLHD is a measure which is robust to expression changes, facial occlusions, and depth outliers. The proposed face recognition system performances are evaluated under expression changes and facial occlusions.

Intuitive Pointing Position Estimation for Large Scale Display Interaction in Top-View Depth Images

In this paper, we propose an intuitive pointing position estimation method for large scale display interaction in top-view depth images. The depth sensor is mounted above the users’ head in order to avoid the sensor occluding the display. In order to estimate the pointing position, we detect the user’s head and estimate the position of the user’s eye. To calculate the center of the head, we propose a head segmentation method. We use an iterative binary partitioning method and a one-to-one correspondence method to detect and track the hands, respectively. The 3D positions of the head and hands were converted to the real world coordinates and the pointing position was estimated on the eye-hand ray intersecting with the large screen. Experimental results show that we improve the head detection rate applying our head segmentation method. Also, we calculate the pointing direction accuracy and the proposed method has a good performance compared with conventional methods even in dark environments.