Paper
3 June 1997 Analysis of perplexing situations in word processor work using facial image sequence
Takayuki Kamitani, Yoji Marutani
Author Affiliations +
Proceedings Volume 3016, Human Vision and Electronic Imaging II; (1997) https://doi.org/10.1117/12.274528
Event: Electronic Imaging '97, 1997, San Jose, CA, United States
Abstract
Computer users often feel difficulty in operating. For this reason, it is desirable to make the computer detect the operator's perplex situations and carry out the kindness action to the operator. We propose the method for recognizing the perplex situations in word processor work. Firstly, the perplexed behaviors were picked up by observing the subjects in word processor work. As the result of the observation, it was made clear that the perplexed behaviors were shown in the motion of the head and keyboard operation rather than facial expression. Secondly, the head motions in x, y, z and (Theta) directions were captured in real time by chasing both pupils through the use of image processing. In the system, the processing speed is enhanced by reducing image data. The behaviors are converted to the series of vectors which have the moving speed of head. Thirdly, the distances between unknown input motion patterns and the template patterns of the vector sequences were calculated by DP matching. As the result of DP matching, it was made clear that each head motion was identified. The proposed method can be applied to the development of the software which responses automatically when the operator falls into the perplex situations.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Takayuki Kamitani and Yoji Marutani "Analysis of perplexing situations in word processor work using facial image sequence", Proc. SPIE 3016, Human Vision and Electronic Imaging II, (3 June 1997); https://doi.org/10.1117/12.274528
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KEYWORDS
Head

Image processing

Cameras

CRTs

Image enhancement

Software development

Binary data

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