Open AccessDirect three‐dimensional head pose estimation from Kinect‐type sensors
Author(s) -
Kondori F.A.,
Yousefi Sh.,
Li H.
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2013.2489
Subject(s) - head (geology) , pose , artificial intelligence , computer vision , computer science , estimation , pattern recognition (psychology) , engineering , geology , geomorphology , systems engineering
A direct method for recovering three‐dimensional (3D) head motion parameters from a sequence of range images acquired by Kinect sensors is presented. Based on the range images, a new version of the optical flow constraint equation is derived, which can be used to directly estimate 3D motion parameters without any need of imposing other constraints. Since all calculations with the new constraint equation are based on the range images, Z ( x , y , t ), the existing techniques and experiences developed and accumulated on the topic of motion from optical flow can be directly applied simply by treating the range images as normal intensity images I ( x , y , t ). In this reported work, it is demonstrated how to employ the new optical flow constraint equation to recover the 3D motion of a moving head from the sequences of range images, and furthermore, how to use an old trick to handle the case when the optical flow is large. It is shown, in the end, that the performance of the proposed approach is comparable with that of some of the state‐of‐the‐art approaches that use range data to recover 3D motion parameters.