A qualitative approach to classifying head and eye pose
نویسنده
چکیده
The goal of this work is to classify the focus of attention of a subject who is switching his or her attention between a number of surrounding objects. The specific application is to classify the focus of attention of a car driver as straight-ahead, towards the rear-view mirror, towards the dashboard etc. An explicit quantitative approach to this problem requires (a) a priori information about the interior geometry of the car and the calibration of the camera, and (b) accurate computation of the subjectś location and eye direction. This paper describes a qualitative approach. The subject is observed over an extended period of time, and a p̈ose-space histogramı̈s used to record the frequency with which particular head poses occur. For observation of a car driver, peaks will appear in the histogram corresponding to the most frequently viewed directions–straight-ahead and toward the mirrors. Each peak is labelled, and the head pose of the driver in all subsequent images is then classified by use of the histogram. The head pose classification is refined by a qualitative measurement of the eye pose. IEEE Workshop on Applications of Computer Vision, Oct 1998, pp. 208-213 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c ©Mitsubishi Electric Research Laboratories, Inc., 1998 201 Broadway, Cambridge, Massachusetts 02139
منابع مشابه
Head and eye gaze dynamics during visual attention shifts in complex environments.
The dynamics of overt visual attention shifts evoke certain patterns of responses in eye and head movements. In this work, we detail novel findings regarding the interaction of eye gaze and head pose under various attention-switching conditions in complex environments and safety critical tasks such as driving. In particular, we find that sudden, bottom-up visual cues in the periphery evoke a di...
متن کاملA Head Pose-free Approach for Appearance-based Gaze Estimation
(a) (b) (c) Figure 1: 2-D illustration of relationship between gaze direction and head pose. (a) Under a fixed head pose (r0, t0), gaze direction α can be estimated from appearance. (b) To obtain α under another head pose (r̂, t̂), the estimated α ′ should be corrected because of captured eye appearance distortion. (c) Under head pose (r̂, t̂), gaze direction under WCS should be further compensated...
متن کاملFast Multiple Camera Head Pose Tracking
This paper presents a multiple camera system to determine the head pose of people in an indoor setting. Our approach extends current eye tracking techniques from a single camera system to a multiple camera system. The head pose of a person is determined by triangulating multiple facial features that are obtained in real-time from eye trackers. Our work is unique in that it allows us to observe ...
متن کاملA Study on Gaze Estimation Using Head and Body Pose Information
Gaze estimation from an image is an important technique for tasks such as driver monitoring and measuring of advertising effectiveness. For this, most existing methods require a high quality image of eyes. However, It is difficult to obtain the eye images when eye occlusion occurs due to sunglasses or face rotation. Another approach approximates head directions to gaze directions. However, the ...
متن کاملA robust head pose tracking system based on multiple cameras
Tracking human head pose has many applications such as building input devices for game players and for the disabled. Traditional vision methods detect the image of the head to deduce its pose. Our approach is the reverse, we attach cameras to the head so head pose tracking becomes camera pose tracking. The main problem with camera centered vision based pose tracking is that, if one camera is us...
متن کامل