No abstract

This paper presents a wearable eye tracker that tracks points of interests of user at videostream showed at smartphone screen. The system consists head-mounted case for smartphone, point of interest detection algorithm, the software developed for this purposes, and Android smartphone used to show videostream, estimate point of interests at video, and log estimated data into device internal memory.

Recently, various systems of tracking the direction of a person's gaze have been of great interest. As a rule, these systems have a complex structure, and also use additional sources of illumination. This article discusses eye tracking methods, and proposes a method for tracking and determining the shape of the iris.

This paper proposes the method for real time determining three-dimensional coordinates of human body parts from RGB-D stream. Proposed method represent a combined solution in which deep learning and depth map analysis are used.

This paper is devoted to improving the accuracy of human pulse measurement by RGB video stream analysis. For this purpose, a study was conducted the influence of the size, location and stability of the region of interest on contactless human pulse measurement results.