Charles Sturt University
Charles Sturt University

Object Detection and Background Modeling

M. Paul


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.

Examples of object detection

Object Detection from PETS2006 sequence

Selected Publication

Salesian M, Paul M, "Fusion of Foreground Object, Spatial and Frequency Domain Motion Information for Video Summarization", To Be Published in Lecture Note in Computer Science, 2015.