Title :
Camera motion detection for mobile smart cameras using segmented edge-based optical flow
Author :
Mahabalagiri, Anvith ; Ozcan, Koray ; Velipasalar, Senem
Author_Institution :
Electr. Eng. & Comput. Sci. Dept., Syracuse Univ., Syracuse, NY, USA
Abstract :
Determining camera motion is a challenging task in applications involving mobile smart cameras. With widespread use of cameras in mobile applications, analyzing motion-based information have become important. Optical flow has been a popular technique in determining camera motion. However, the use of traditional optical flow techniques can be computationally quite expensive and impractical for embedded smart cameras with limited processing power, The aim of this paper is to provide an effective and computationally efficient optical flow technique to determine the camera motion direction. This technique is based on the segmentation of edge features, and has been implemented on an actual embedded platform. We will show that the systematic segmentation of edge features not only reduces computation time drastically, but also provides sufficient details in determining basic camera motion patterns.
Keywords :
cameras; edge detection; feature extraction; image segmentation; image sequences; camera motion detection; camera motion direction; edge feature segmentation; embedded smart cameras; mobile smart cameras; motion-based information; segmented edge-based optical flow; systematic segmentation; Cameras; Image edge detection; Motion segmentation; Optical imaging; Optical sensors; Robot vision systems; Vectors;
Conference_Titel :
Advanced Video and Signal Based Surveillance (AVSS), 2014 11th IEEE International Conference on
Conference_Location :
Seoul
DOI :
10.1109/AVSS.2014.6918680