Unsupervised Deep Context Prediction for Background Foreground Separation

Understand

In many advanced video based applications background modeling is a pre-processing step to eliminate redundant data, for instance in tracking or video surveillance applications.

• Over the past years background subtraction is usually based on low level or hand-crafted features such as raw color components, gradients, or local binary patterns.
• The background subtraction algorithms performance suffer in the presence of various challenges such as dynamic backgrounds, photometric variations, camera jitters, and shadows.
• To handle these challenges for the purpose of accurate background modeling we propose a unified framework based on the algorithm of image inpainting.