A Fuzzy Moving Object Estimation Using Infrared TOF Camera

Abstract

This paper describes an object classification method using infrared TOF camera. The method detects moving objects from a distance distribution data. The objects are extracted by k-means clustering method based on fuzzy inference. To classify them, fuzzy if-then rules and fuzzy membership functions are derived from the knowledge of human characteristics. The system classifies them to toddler, child, adult and the other object such as baggage and animal. In the experiment, we employed seven volunteers, two dogs and a box. The system successfully classified them.

Keywords::

• Fuzzy Inference
• Infrared TOF Camera
• Human Detection
• Night Vision

Additional information

Notes on contributors

Takahiro Takeda

Takahiro Takeda received the B.E. in computer engineering (2009) from University of Hyogo, and M. E. in computer engineering (2011) from Graduate school of Engineering, University of Hyogo, Hyogo, Japan. He is now a Ph. D candidate with the Division of Computer Engineering, Graduated School of Engineering in University of Hyogo, Japan. His researches interests include biometrics and fuzzy logic.

Kei Kuramoto

Syoji Kobashi received his B.E. in electronics (1995), M.E. (1997) and D.E. (2000) from the Himeji Institute of Technology, Hyogo, Japan. He is currently an associate professor of Graduate School of Engineering, University of Hyogo, and an associate guest professor of WPI Immunology frontier research center, Osaka University, Japan. His research interests include soft computing based medical image processing.

Syoji Kobashi

Kei Kuramoto received the B.S. degree in Nara University of Education and M.S. degree in NAIST, Nara, Japan, and Dr. in Kyoto University. During 2005–2008, he stayed in TCRL, Toyota Central R&D Labs., Inc. to study computational chemistry. He is currently an associate professor of Graduate School of Engineering, University of Hyogo, and an associate guest professor of WPI Immunology frontier research center, Osaka University. His research interests are in quantum chemistry calculations.

Yutaka Hata

Yutaka Hata received the B.E. degree (Electronics) in 1984, the M.E. degree (Electrical Engineering and Electronics) in 1986 and the Ph.D. (Doctor of Engineering) in 1989 from Himeji Institute of Technology, Japan. He is currently a Professor in the Graduate School of Engineering, University of Hyogo, Japan. He spent one year in BISC Group, University of California at Berkeley from 1995 to 1996 as a visiting scholar. His research interests are in medical system, health monitoring system, fuzzy system and Immune system. He has received 13 international awards such as the Franklin V. Taylor Best Paper Award (IEEE SMC 2009), Biomedical Wellness Award (SPIE Defense, Security, and Sensing 2010) etc. He is an Editor-in-chief: International Journal of Intelligent Computing in Medical Sciences and Image Processing, USA and 5 Journal editors.

He is a member of the Institute of Electronics, Information and Communication Engineers of Japan and Japan Society for Fuzzy Theory and Systems, The Japan Society of Medical Electronics and Biological Engineering, Biomedical Fuzzy Systems Association and an IEEE Fellow.