Pedestrian detection by computer vision
This document describes work aimed at determining whether the detection, by computer vision, of pedestrians waiting at signal-controlled road crossings could be made sufficiently reliable and affordable, using currently available technology, so as to be suitable for widespread use in traffic control systems. The work starts by examining the need for pedestrian detection in traffic control systems and then goes onto look at the specific problems of applying a vision system to the detection task. The most important distinctive features of the pedestrian detection task addressed in this work are: • The operating conditions are an outdoor environment with no constraints on factors such as variation in illumination, presence of shadows and the effects of adverse weather. • Pedestrians may be moving or static and are not limited to certain orientations or to movement in a single direction. • The number of pedestrians to be monitored is not restricted such that the vision system must cope with the monitoring of multiple targets concurrently. • The background scene is complex and so contains image features that tend to distract a vision system from the successful detection of pedestrians. • Pedestrian attire is unconstrained so detection must occur even when details of pedestrian shape are hidden by items such as coats and hats. • The camera's position is such that assumptions commonly used by vision systems to avoid the effects of occlusion, perspective and viewpoint variation are not valid. •The implementation cost of the system, in moderate volumes, must be realistic for widespread installation. A review of relevant prior art in computer vision with respect to the above demands is presented. Thereafter techniques developed by the author to overcome these difficulties are developed and evaluated over an extensive test set of image sequences representative of the range of conditions found in the real world. The work has resulted in the development of a vision system which has been shown to attain a useful level of performance under a wide range of environmental and transportation conditions. This was achieved, in real-time, using low-cost processing and sensor components so demonstrating the viability of developing the results of this work into a practical detector.