Title :
A Hand Grasped Object Segmentation Method Using Kinect Sensor and Body Dimension Database
Author :
Hisatsuka, Naruyuki ; Samejima, Ippei ; Kagami, Satoshi ; Kouchi, Makiko ; Takemura, Hiroshi
Author_Institution :
Digital Human Res. Center, Nat. Inst. of Adv. Ind. Sci. & Technol., Tokyo, Japan
Abstract :
This paper proposes a method to segment out a hand grasped object from human region obtained from Kinect sensor by using body dimension database. Having dataset of human body dimensions, Multiple Regression Analysis is applied to find out the best explanatory variables for forearm and upper arm length. As a result, "body height" is selected. In order to measure "body height" accurately, Kinect depth image is utilized to search with kinematical result obtained from Kinect software. After estimating wrist position, we can segment out hand grasped region. Methods and experimental results are shown.
Keywords :
height measurement; image segmentation; image sensors; pose estimation; regression analysis; Kinect depth image; Kinect sensor; Kinect software; body dimension database; body height measurement; forearm; hand grasped object segmentation; hand grasped region segmentation; human body dimensions dataset; human region; kinematical result; multiple regression analysis; upper arm length; wrist position estimation; Data mining; Databases; Estimation; Image segmentation; Length measurement; Object segmentation; Wrist; Body Dimensions; Kinect; Segmentation;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location :
Manchester
DOI :
10.1109/SMC.2013.529
