A system for small target detection, tracking, and classification

Abstract

A system is developed for small target detection, tracking and classification. The specific application of interest is an automatic headlight dimming system (AutoDim) for automotive night-time driving use. The burden of controlling the state of the vehicle's headlights (high or low beam) is taken away from the driver and shifted on to the AutoDim system. AutoDim's decision as to whether or not to change the state of the headlights is made from visual information obtained from a low-cost, low-resolution CMOS video camera. The targets of potential interest (i.e. light sources) are detected based on their brightness, geometric and spatial attributes. However, this also detects segments that do not correspond to the vehicular tail/headlights. Typical sources of error include street lights, reflected light, sky light, etc. To eliminate such errors, and to discriminate vehicular tail/headlight sources from other light sources, a non-parametric classifier is employed using a feature set that includes the light source's spectral distribution and temporal track record, in addition to the attributes used for detection.