Long-Term Background Reconstruction with Camera in Motion

Abstract

Obtaining a dynamically reconstructed background sprite image is an important and challenging task for video applications such as object-based video coding, tracking and video object segmentation. This paper proposes a novel system for video background reconstruction with camera in motion.Firstly, the proposed algorithm uses feature point pairs from current frame and a reference frame for reliable Global Motion Estimation (GME) where a dynamic reference frame update strategy is utilized. Once the global motion transformation matrix is obtained, each frame is warped into a projective plane where a statistic-based background modeling algorithm is applied and the background sprite image is produced. Compared with conventional sprite generation methods, the proposed algorithm:(1) provides efficient and reliable GME using feature points;(2) significantly reduces the accumulated warping error by a dynamic reference frame update mechanism; (3)produces accurate background pixel reconstruction using a statistic analytical model. The experimental results are presented and analyzed to show the robustness and accuracy of the proposed system.

An Efficient Background Reconstruction Based Coding Method for Surveillance Videos Captured by Moving Camera

“…Therefore, the sprite technique in [1][2] provides an efficient and concise method for the representation of the background objects throughout the video sequence. In [3], the authors proposed a robust online scene background reconstruction where optical flow and pixel intensity distribution are utilized. In [4], a fast and robust sprite generation is proposed.…”