Pedestrian detection by means of far-infrared stereo vision

Pedestrian Recognition Suitable for Night Vision Systems

Nowadays, pedestrian recognition in far-infrared images toward realizing a night vision system becomes a hot topic. However, sufficient performance could not be achieved by conventional schemes for pedestrian recognition in farinfrared images. Since the properties of far-infrared images are different from visible images, it is not known what kind of scheme is suitable for pedestrian recognition...

Pedestrian Validation in Infrared Images by Means of Active Contours and Neural Networks

This paper presents two different modules for the validation of human shape presence in far-infrared images. These modules are part of a more complex system aimed at the detection of pedestrians by means of the simultaneous use of two stereo vision systems in both far-infrared and daylight domains. The first module detects the presence of a human shape in a list of areas of attention using acti...

Pedestrian Detection with near and Far Infrared Night Vision Enhancement

Nighttime Foreground Pedestrian Detection Based on Three-Dimensional Voxel Surface Model

Pedestrian detection is among the most frequently-used preprocessing tasks in many surveillance application fields, from low-level people counting to high-level scene understanding. Even though many approaches perform well in the daytime with sufficient illumination, pedestrian detection at night is still a critical and challenging problem for video surveillance systems. To respond to this need...

Night Vision: Requirements and possible roadmap for FIR and NIR systems

A Night Vision system must increase visibility in situations where only low beam headlights can be used today. As pedestrians and animals have the highest risk increase in night time traffic due to darkness, the ability of detecting those objects should be the main performance criteria, and the system must remain effective when facing the headlights of oncoming vehicles. Far infrared system has...