Title :
Gesture recognition based on depth difference distribution
Author :
Peng Zhang ; Tao Li ; Huaixin Xiong ; Linyan Liang
Author_Institution :
RICOH Software Res. Center, Beijing, China
Abstract :
We present a novel motion descriptor for gesture recognition based on depth camera. Since each object motion leads to a specific depth change characterized by depth difference, we can recognize object motion via Depth Difference Distribution (DDD) in object region. The DDD is approximated by DDD descriptor in three steps. First, each pixel´s depth difference value is quantified into Depth Difference (DD) codes. Second, the object region is separate into several sub-regions. Third, in each sub-region, a vector is generated to describe the distribution of each DD code. The vectors of each DD code in each sub-region are cascaded into the final DDD descriptor to approximate the depth difference distribution caused by object motion. DDD descriptor is a combination of both motion and shape information. Experiment shows a robust gesture detection performance is achieved within large distance and view angle variation range.
Keywords :
gesture recognition; image motion analysis; object detection; object recognition; shape recognition; vectors; DD code; DDD descriptor; depth camera; depth change; depth difference distribution; gesture detection performance; gesture recognition; motion descriptor; motion information; object motion recognition; object region; pixel depth difference value; shape information; vector; view angle variation range; Cameras; Computer vision; Gesture recognition; Humans; Real-time systems; Robustness; Shape;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4