An Efficient Multi-View Panoramic Imaging and Extra Compression of Surveillance Cameras’ Footage Using Stitching

Abstract

Saving data stored and transferred is a critical topic in modern era, especially after the evolution in the numbers of surveillance cameras in the world. So an extra level of compression is needed to contribute in solving the problem of the huge data produced by those cameras. The proposed system: “An Efficient multi-view panoramic imaging and Extra Compression of surveillance cameras’ footage using Stitching” (ECS) aims to contribute in the solution of this problem by merging feature extraction stitching techniques with geometric relational matrix calculations. ECS creates a new real-time efficient stitching algorithm to minimize the sending and storing of the redundant pixels between the footage of the surveillance cameras. The limitations of using stitching on video footage and not on still images is due to the high complexities of stitching algorithms; the proposed system, in this paper, uses the projective affine transformation matrix between images of camera footage to reduce this limitations. The work presented in this paper introduces, for the first time, an algorithm to reconstruct images of each camera from the panoramic view. The experimental work of this research tests multiple feature extraction algorithms for stitching; Scale Invariant Feature Transform (SIFT), Speed Up Robust Feature (SURF) and Oriented FAST and Rotated BRIEF (ORB) with different order of stitching, and the amount of compression per image after reconstruction is analyzed. Moreover, the panoramic view is mostly a better monitoring option rather than multiple monitors in complex surveillance cameras’ control rooms. Experimental results show that the proposed method could be faster than other state-of-the-art image stitching methods and accurate panoramic image. The system also gives a better visual effect in a large view panorama due to the high speed real time stitching introduced in this paper.