PT Journal
AU Sergio Escalera
   Jordi Gonzalez
   Xavier Baro
   Jamie Shotton
TI Guest Editor Introduction to the Special Issue on Multimodal Human Pose Recovery and Behavior Analysis
SO IEEE Transactions on Pattern Analysis and Machine Intelligence
JI TPAMI
PY 2016
BP 1489
EP 1491
VL 28
DI 10.1109/TPAMI.2016.2557878
AB The sixteen papers in this special section focus on human pose recovery and behavior analysis (HuPBA). This is one of the most challenging topics in computer vision, pattern analysis, and machine learning. It is of critical importance for application areas that include gaming, computer interaction, human robot interaction, security, commerce, assistive technologies and rehabilitation, sports, sign language recognition, and driver assistance technology, to mention just a few. In essence, HuPBA requires dealing with the articulated nature of the human body, changes in appearance due to clothing, and the inherent problems of clutter scenes, such as background artifacts, occlusions, and illumination changes. These papers represent the most recent research in this field, including new methods considering still images, image sequences, depth data, stereo vision, 3D vision, audio, and IMUs, among others.
ER