TY - GEN
T1 - Auditory and visual integration based localization and tracking of humans in daily-life environments
AU - Kim, Hyun Don
AU - Komatani, Kazunori
AU - Ogata, Tetsuya
AU - Okuno, Hiroshi G.
PY - 2007/12/1
Y1 - 2007/12/1
N2 - The purpose of this research is to develop techniques that enable robots to choose and track a desired person for interaction in daily-life environments. Therefore, localizing multiple moving sounds and human faces is necessary so that robots can locate a desired person. For sound source localization, we used a cross-power spectrum phase analysis (CSP) method and showed that CSP can localize sound sources only using two microphones and does not need impulse response data. An expectation-maximization (EM) algorithm was shown to enable a robot to cope with multiple moving sound sources. For face localization, we developed a method that can reliably detect several faces using the skin color classification obtained by using the EM algorithm. To deal with a change in color state according to illumination condition and various skin colors, the robot can obtain new skin color features of faces detected by OpenCV, an open vision library, for detecting human faces. Finally, we developed a probability based method to integrate auditory and visual information and to produce a reliable tracking path in real time. Furthermore, the developed system chose and tracked people while dealing with various background noises that are considered loud, even in the daily-life environments.
AB - The purpose of this research is to develop techniques that enable robots to choose and track a desired person for interaction in daily-life environments. Therefore, localizing multiple moving sounds and human faces is necessary so that robots can locate a desired person. For sound source localization, we used a cross-power spectrum phase analysis (CSP) method and showed that CSP can localize sound sources only using two microphones and does not need impulse response data. An expectation-maximization (EM) algorithm was shown to enable a robot to cope with multiple moving sound sources. For face localization, we developed a method that can reliably detect several faces using the skin color classification obtained by using the EM algorithm. To deal with a change in color state according to illumination condition and various skin colors, the robot can obtain new skin color features of faces detected by OpenCV, an open vision library, for detecting human faces. Finally, we developed a probability based method to integrate auditory and visual information and to produce a reliable tracking path in real time. Furthermore, the developed system chose and tracked people while dealing with various background noises that are considered loud, even in the daily-life environments.
UR - http://www.scopus.com/inward/record.url?scp=50149088675&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=50149088675&partnerID=8YFLogxK
U2 - 10.1109/IROS.2007.4399331
DO - 10.1109/IROS.2007.4399331
M3 - Conference contribution
AN - SCOPUS:50149088675
SN - 1424409128
SN - 9781424409129
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 2021
EP - 2027
BT - Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
T2 - 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
Y2 - 29 October 2007 through 2 November 2007
ER -