PAISAJES PARADISIACOS

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Traditional cross-ratio methods (TCR) project a light pattern and use invariant properties of projective geometry to estimate the gaze position. Advantages of the TCR methods include robustness to large head movements and in general requires just a one time per user calibration. However, the accuracy of TCR methods decay significantly for head movements along the camera optical axis, mainly due to the angular difference between the optical and visual axis of the eye. In this paper we propose a depth compensation cross-ratio (DCR) method that improves the accuracy of TCR methods for large head depth variations. Our solution compensates the angular offset using a 2D onscreen vector computed from a simple calibration procedure. The length of the 2D vector, which varies with head distance, is adjusted by a scale factor that is estimated from relative size variations of the corneal reflection pattern. The proposed DCR solution was compared to a TCR method using synthetic and real data from 2 users. An average improvement of 40% was observed with synthetic data, and 8% with the real data.

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The intuitive user interfaces of PCs and PDAs, such as pen display and touch panel, have become widely used in recent times. In this study, we have developed an eye-tracking pen display based on the stereo bright pupil technique. First, the bright pupil camera was developed by examining the arrangement of cameras and LEDs for pen display. Next, the gaze estimation method was proposed for the stereo bright pupil camera, which enables one point calibration. Then, the prototype of the eyetracking pen display was developed. The accuracy of the system was approximately 0.7° on average, which is sufficient for human interaction support. We also developed an eye-tracking tabletop as an application of the proposed stereo bright pupil technique.

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A challenging goal today is the use of computer networking and advanced monitoring technologies to extend human intellectual capabilities in medical decision making. Modern commercial eye trackers are used in many of research fields, but the improvement of eye tracking technology, in terms of precision on the eye movements capture, has led to consider the eye tracker as a tool for vision analysis, so that its application in medical research, e.g. in ophthalmology, cognitive psychology and in neuroscience has grown considerably. The improvements of the human eye tracker interface become more and more important to allow medical doctors to increase their diagnosis capacity, especially if the interface allows them to remotely administer the clinical tests more appropriate for the problem at hand. In this paper, we propose a client/server eye tracking system that provides an interactive system for monitoring patients eye movements depending on the clinical test administered by the medical doctors. The system supports the retrieval of the gaze information and provides statistics to both medical research and disease diagnosis.

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