Synopsis
Object detection from the complex and dynamically changing background is still a challenging task in the field of computer vision. Adaptive background modeling based object detection techniques are widely used in machine vision applications for handling the challenges of real-world multimodal background. But they are constrained to specific environment due to relying on environment specific parameters, and their performances also fluctuate across different operating speeds. Camera motions of a scene makes dynamic background modeling more complicated. We are focusing on dynamic background modeling in challenging environments and their applications in different fields.
Object Detection from PETS2006 sequence