A monocular wide-field speed sensor inspired by the crabs’ visual system for traffic analysis

Abstract

The development of visual sensors for traffic analysis can benefit from mimicking two fundamental aspects of the visual system of crabs: their panoramic vision and their visual processing strategy adapted to a flat world. First, the use of omnidirectional cameras in urban environments allows for analyzing the simultaneous movement of many objects of interest over broad areas. This would reduce the costs and complications associated with infrastructure: installation, synchronization, maintenance, and operation of traditional vision systems that use multiple cameras with a limited field of view. Second, in urban traffic analysis, the objects of interest (e.g., vehicles and pedestrians) move on the ground surface. This constraint allows the calculation of the 3D trajectory of the vehicles using a single camera without the need to use binocular vision techniques. The main contribution of this work is to show that the strategy used by crabs to visually analyze their habitat (monocular omnidirectional vision with the assumption of a flat world ) is useful for developing a simple and effective method to estimate the speed of vehicles on long trajectories in urban environments. It is shown that the proposed method estimates the speed with a root mean squared error of 2.7 km/h.