Stereoscopic video system with embedded high spatial resolution images using two channels for transmission

Abstract

Teleoperation requires both wide vision to recognize a whole workspace and fine vision to recognize the precise structure of objects which an operator wants to see. In order to achieve high operational efficiency in teleoperation, we have developed the Q stereoscopic video system which is constructed of four sets of video cameras and monitors. It requires four video channels to transmit video signals. However, four channels are not always available for a video system because of the limitation of the number of radio channels when multiple systems are used at the same time. Therefore we have tried to reduce the number of channels on this system by sending images from the right and left cameras alternately by field. In experiment 1, we compared the acuity of depth perception under three kinds of stereoscopic video systems, the original Q stereoscopic video system, the Q stereoscopic video system with two channel transmission, and the conventional stereoscopic video system. As the result of the experiment, the original Q stereoscopic video system enabled us to perceive depth most precisely, the Q stereoscopic video system with two channel transmission less so, and the conventional stereoscopic video system even less. In experiment 2, we compared the Q stereoscopic video system with two channel transmission to the original Q stereoscopic video system. The result showed that the operators were able to work more efficiently under the original Q stereoscopic video system than under the Q stereoscopic video system with two channel transmissions. In experiment 3, we compared the Q stereoscopic video system with two channel transmission to the conventional stereoscopic video system. It was found out in this study that the new stereoscopic video system we developed enabled operators to work more efficiently and to perceive depth more precisely than the conventional stereoscopic video system, although the number of channels for image transmission of this system was equal to that of the conventional stereoscopic video system.

Dual-sensor foveated imaging system

“…The second category is the algorithmic approach in which foveation techniques are applied primarily to image processing [2,7], video encoding [6,8], and graphics rendering [9 -11] to achieve real-time video communication through low-bandwidth networks and to save data transmission bandwidth and processing resources. For instance, Geisler and Perry demonstrated a three times greater compression ratio in multiresolution images͞videos [8]; Ienaga et al described a stereoscopic video transmission system with embedded high-resolution fovea images to accelerate the image processing and to reduce the bandwidth requirement [2]; several researchers applied perceptually driven foveation treatments to 3D graphics rendering such a levelof-detail management and polygon reduction in 3D models based on the view eccentricity [9 -11]. Murphy and Duchowski demonstrated that the rendering speed can be significantly accelerated by only rendering high levels of detail of a 3D scene around a user's gaze direction in virtual environments [10]; Luebeke et al demonstrated that 2-6 times fewer polygons can produce the similar rendering effect in perceived model resolution [11].…”

“…Real-time acquisition of high-resolution, wide field of view (FOV), and high dynamic range (HDR) images is essential for many vision-based applications, ranging from the macroscale imaging in surveillance [1], teleconferencing [2], and robot navigation [3], to micrometer or submicrometer-scale imaging in biomedical imaging [4] and vision-guided microfabrication [5]. Although detector technologies have improved dramatically over the past decades, many imaging systems are limited by their performances on FOV, resolution, speed, and dynamic range.…”

Design of a Foveated Imaging System Using a Two-Axis MEMS Mirror

“…These means, by making tradeoffs between the viewer's primary and peripheral regions of interest, have been used for image processing, video coding [3] and stereoscopic displays [4] to accelerate the image processing and to reduce the bandwidth requirement.…”