TY - GEN
T1 - Camera motion detection for mobile smart cameras using segmented edge-based optical flow
AU - Mahabalagiri, Anvith
AU - Ozcan, Koray
AU - Velipasalar, Senem
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/8
Y1 - 2014/10/8
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84909952051&partnerID=8YFLogxK
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U2 - 10.1109/AVSS.2014.6918680
DO - 10.1109/AVSS.2014.6918680
M3 - Conference contribution
AN - SCOPUS:84909952051
T3 - 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014
SP - 271
EP - 276
BT - 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014
Y2 - 26 August 2014 through 29 August 2014
ER -