Quasi-Parallax for Nearly Parallel Frontal Eyes: A Possible Role of Binocular Overlap During Rapid Locomotion

Long-Range Binocular Vision Target Geolocation Using Handheld Electronic Devices in Outdoor Environment

Binocular vision is a passive method of simulating the human visual principle to perceive the distance to a target. Traditional binocular vision applied to target localization is usually suitable for short-range area and indoor environment. This paper presents a novel vision-based geolocation method for long-range targets in outdoor environment, using handheld electronic devices such as smart phones and tablets. This method solves the problems in long-range localization and determining geographic coordinates of the targets in outdoor environment. It is noted that these sensors necessary for binocular vision geolocation such as the camera, GPS, and inertial measurement unit (IMU), are intergrated in these handheld electronic devices. This method, employing binocular localization model and coordinate transformations, is provided for these handheld electronic devices to obtain the GPS coordinates of the targets. Finally, two types of handheld electronic devices are used to conduct the experiments for targets in long range up to 500m. The experimental results show that this method yields the target geolocation accuracy along horizontal direction with nearly 20m, achieving comparable or even better performance than monocular vision methods.

Frontally placed eyes versus laterally placed eyes: computational comparison of their functions for ego-motion estimation

Both frontally placed eyes and laterally placed eyes are popular in nature, and although which one is better could be one of the most intuitive questions to ask, it could also be the hardest question to answer. Their most obvious difference is that, at least as supposed in the computer vision community, stereopsis plays the central role in the visual system composed of frontally placed eyes (or cameras); however, it is not available in the lateral configuration due to the lack of overlap between the visual fields. As a result, researchers have adopted completely different approaches to model the two configurations and developed computational mimics of them to address various vision problems. Recently, the advent of novel quasi-parallax conception unifies the ego-motion estimation procedure of these two eye configurations into the same framework and makes systematic comparison feasible. In this paper, we intend to establish the computational superiority of eye topography from the perspective of ego-motion estimation. Specifically, quasi-parallax is applied to fuse motion cues from individual cameras at an early stage, at the pixel level, and to recover the translation and rotation separately with high accuracy and efficiency without the need of feature matching. Furthermore, its applicability on the extended sideways arrangements is studied successfully to make our comparison more general and insightful. Extensive experiments on both synthetic and real data have been done, and the computational superiority of the lateral configuration is verified.