Paper Info
Title
TV remote control using human hand motion based on optical flow system
Abstract
Motion recognition systems have been widely developed in the field of human computer interaction. Methods, such as pointing, dynamic gesture and static gesture or hand held devices have been proposed for motion recognition. The motion recognition systems have been gradually adapted to home appliances in our daily. In this paper, we focus on TV interaction, since the device is a recent representative multimedia device applying the motion technique. Most motion recognition systems utilize 3D data, such as horizontal, vertical and depth information by stereo camera or ToF (Time of Flight) camera. However, this paper proposes the different techniques for human-TV interaction. We propose an optical flow based motion recognition system that provides direction and speed, in addition to the position of the moving target in real time. These factors are useful in recognizing human motion more effectively and more dynamically. Therefore, we design the natural interaction for human-TV using these motion data. The calculation process of optical flow is outside the scope of this paper. This real time optical flow calculation is implemented using the FPGA chip supporting parallel processing by a hardware team in our laboratory. We propose a method for human motion recognition based on real time optical flow system.
Year
DOI
Venue
2012
10.1007/978-3-642-31137-6_24
ICCSA (3)
Keywords
Field
DocType
human motion,motion recognition,motion data,tv interaction,human hand motion,motion technique,human motion recognition,motion recognition system,optical flow system,human computer interaction,optical flow,tv remote control,real time
Stereo camera,Computer vision,Remote control,Motion recognition,Computer science,Gesture,Real-time operating system,Artificial intelligence,Motion estimation,Optical flow,Match moving
Conference
Volume
ISSN
Citations 
7335
0302-9743
3
PageRank 
References 
Authors
0.40
10
4
Name
Order
Citations
PageRank
Soonmook Jeong1243.42
Taehoun Song2233.04
Keyho Kwon3113.05
Jae Wook Jeon456577.35