Depth Extended Online RPCA for Robust Background Subtraction

Introduction

RPCA presents the limitations of computational and memory issues due to the batch optimization methods, and hence it cannot process high dimensional data. Recent research on RPCA methods such as Online RPCA (OR-PCA) alleviates the traditional RPCA limitations. However, OR-PCA using only color or intensity features shows a weak performance specially when the background and foreground objects have a similar color or shadows appear in the background scen . To handlethese challenges, this paper presents an extension of OR-PCA with the integration of depth and color information for robust background subtraction. Depth is less affected by shadows or background/foreground color saturation issues. However, the foreground object may not be detected when it is far from the camera field as depth is less useful without color information. We show that the OR-PCA including spatiotemporal constraints provides accurate segmentation with the utilization of both color and depth features.

Principle

Figure 1 : Depth Extended Online RPCA with Spatiotemporal Constraints for Robust Background Subtraction

Publication

Journal

S. Javed, S. Oh, T. Bouwmans, S. Jung, "Robust Background Subtraction to Global Illumination Changes via Multiple Features based OR-PCA with MRF", Journal of Electronic Imaging, 2015. [pdf]

Conference

S. Javed, T. Bouwmans, S. Jung, “Combining ARF and OR-PCA Background Subtraction of Noisy Videos”, International Conference in Image Analysis and Applications, ICIAP 2015, Genova, Italy, September 2015. [pdf]

S. Javed, T. Bouwmans, S. Jung, "Depth Extended Online RPCA with Spatiotemporal Constraints for Robust Background Subtraction", Korea-Japan Workshop on Frontiers of Computer Vision, FCV 2015, Mokpo, South Korea, January 2015. [pdf]

S. Javed, A. Sobral, T. Bouwmans, S. Jung, "OR-PCA with Dynamic Feature Selection for Robust Background Subtraction", ACM Symposium On Applied Computing, SAC 2015, Salamanca, Spain, April 2015. [pdf]

S. Javed, A. Sobral, S. Oh, T. Bouwmans, S. Jung, “OR-PCA with MRF for Robust Foreground Detection in Highly Dynamic Backgrounds”, Asian Conference on Computer Vision, ACCV 2014, Singapore, November 2014. [pdf]