Three-dimensional Head Tracking Using Adaptive Local Binary Pattern in Depth Images

Abstract

Recognition of human motions has become a main area of computer vision due to its potential human-computer interface (HCI) and surveillance. Among those existing recognition techniques for human motions, head detection and tracking is basis for all human motion recognitions. Various approaches have been tried to detect and trace the position of human head in two-dimensional (2D) images precisely. However, it is still a challenging problem because the human appearance is too changeable by pose, and images are affected by illumination change. To enhance the performance of head detection and tracking, the real-time three-dimensional (3D) data acquisition sensors such as time-of-flight and Kinect depth sensor are recently used. In this paper, we propose an effective feature extraction method, called adaptive local binary pattern (ALBP), for depth image based applications. Contrasting to well-known conventional local binary pattern (LBP), the proposed ALBP cannot only extract shape information without texture in depth images, but also is invariant distance change in range images. We apply the proposed ALBP for head detection and tracking in depth images to show its effectiveness and its usefulness.

Preschool Education Interactive System Based on Smart Sensor Image Recognition

“…Kim and Yoon proposed an effective feature extraction method in the existing human motion recognition technology, called adaptive local binary pattern (ALBP), for applications based on depth images. Compared with the traditional local binary mode (LBP), this algorithm can not only extract the textureless shape information in the depth image but also has a constant distance in the distance image [6]. Elngar and Kayed also apply face recognition in image recognition technology to vehicle intelligence.…”

Immersive Stereoscopic 3D System with Hand Tracking in Depth Sensor

“…In this paper, we apply augmented reality technology to 3D hand tracking based on stereoscopic 3D system. The proposed system obtains depth map from Microsoft Kinect to generate stereoscopic 3D image and uses depth based 3D tracking technology [10,11]. Next, 3D objects are augmented on the hand that is tracked in 3D space, and augmented reality is applied.…”