COMPUTER VISION FOR INTELLIGENT VEHICLES

Contributor : Cinsu Thomas

ABSTRACT

Vision is the main sense that we use to perceive the structure of the surrounding environment. Due to the large amount of information that an image carries, artificial vision is an extremely powerful way to sense the surroundings also for autonomous robots.

In many indoor applications, such as the navigation of autonomous robots in both structured and unknown settings, vision and active sensors can perform complementary tasks for the recognition of objects, detection of free-space, or check for some specific object characteristics. The recent advances in computational hardware ,such as a higher degree of integration, allows to have machines that can deliver a high computational power ,with fast networking facilities, at an affordable price .In addition to this, current cameras include new important features that allow to address and solve some basic problems directly at the sensor level. The resolution of the sensors has been drastically enhanced. In order to decrease the acquisition and transfer time, new technological solutions can be found in CMOS cameras, with important advantages such as the pixels can be addressed independently like in traditional memories, and their integration on the processing chip seems to be straight forward.

The success, of computational approaches to perception, is demonstrated by the increasing numbers of autonomous systems, that are now being used in structured and controlled industrial environments and, that are now being studied and implemented to work in a more complex and unknown settings .In particular, the last years have witnessed an increasing interest towards the use of vision techniques for perceiving automotive environments, both for highway and urban scenarios, will become a reality in the next decades. Besides the obvious advantages of increasing road safety and improving the quality and efficiency for people and goods mobility, the integration of intelligent features and autonomous functionalities on vehicles will lead to major economical benefits such as reductions in fuel consumption, efficient exploitation of the road network. Furthermore, not only the automotive field is interested in these new technologies, but other sectors as well, each with its own target (industrial vehicles, military systems, mission critical and unmanned rescue robots).