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In this paper, an autonomous multiple target detection and tracking technique for dynamic scenes that are influenced by illumination variations, occlusions and camera instability is proposed. The framework combines a novel Dynamic Reverse Analysis (DRA) approach with an Enhanced Rao-Blackwellized Particle Filter (E-RBPF) for multiple target detection and tracking, respectively. The DRA method, in addition to providing accurate target localization, presents the E-RBPF scheme with costs associated with the differences in intensity caused by illumination variations between consecutive frame pairs in any video of a dynamic scene. The E-RBPF inherently models these costs, thus allowing the framework to (a) adapt learning parameters, (b) distinguish between camera-motion and object-motion, (c) deal with sample degeneracy, (d) provide appropriate appearance compensation during likelihood measurement …