Can DMD obtain a Scene Background in Color?
This work addresses the need for color background models in computer vision applications, but it is incremental as it builds on existing DMD methods by extending them from grayscale to color.
The study tackled the problem of obtaining a colored background model from video frames, which is crucial for applications like video surveillance and computational photography, by proposing a technique that extends Dynamic Mode Decomposition (DMD) to operate in the color domain, and demonstrated its effectiveness on the SBI dataset with qualitative and quantitative results showing successful colored background extraction.
A background model describes a scene without any foreground objects and has a number of applications, ranging from video surveillance to computational photography. Recent studies have introduced the method of Dynamic Mode Decomposition (DMD) for robustly separating video frames into a background model and foreground components. While the method introduced operates by converting color images to grayscale, we in this study propose a technique to obtain the background model in the color domain. The effectiveness of our technique is demonstrated using a publicly available Scene Background Initialisation (SBI) dataset. Our results both qualitatively and quantitatively show that DMD can successfully obtain a colored background model.