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Eye tracking with webcam
Eye tracking with webcam













However, gaze prediction is difficult because the complex interplay between the visual stimulus, the task, and prior knowledge of the visual world which determines eye movements is not yet fully understood Eye movements provide a rich source of information into real-time human visual attention and cognition, and the development of gaze prediction models is of significant interest in computer vision for many years.

Eye tracking with webcam full#

READ FULL TEXT VIEW PDFĪn understanding of human visual attention is essential to many applications in computer vision, computer graphics, computational photography, psychology, sociology, and human-computer interaction. Tool and provide a web server where researchers can upload their images to getĮye tracking results from AMTurk. Saliency dataset for a large number of natural images. Less effort on the part of the researchers. To data gathered in a traditional lab setting, with relatively lower cost and By a combination of careful algorithm and gaming protocolĭesign, our system obtains eye tracking data for saliency prediction comparable Supports large-scale, crowdsourced eye tracking deployed on Amazon Mechanical To address thisĭeficiency, this paper introduces a webcam-based gaze tracking system that Size of these datasets limits the potential for training data intensiveĪlgorithms, and causes overfitting in benchmark evaluation. Smaller than typical datasets for other vision recognition tasks. Therefore, existing saliency prediction datasets are order-of-magnitudes Traditional eye tracking requires specialized hardware, which meansĬollecting gaze data from many observers is expensive, tedious and slow.













Eye tracking with webcam