TY - GEN
T1 - Shot boundary detection using correlation based spectral residual saliency map
AU - Shekar, B. H.
AU - Uma, K. P.
AU - Holla, K. Raghurama
PY - 2016/11/2
Y1 - 2016/11/2
N2 - Information present in videos are used by variety of applications like surveillance, intelligent business analysis, high tech education etc. To harness this vital information segmenting the video to its basic architectural unit is required. This paper proposes an approach for shot identification based on spectral residual. The spectral residual of a video frame is obtained by analysing the log spectrum of the frame. The ability of spectral residual to represent the innovative or novelty part of the frame and to provide consolidated representation of the scene makes it promising for video segmentation. The spatial domain representation of spectral residual gives the saliency map. At the shot boundaries there will be variations in the innovative regions of the adjacent frames. Using the correlation between the saliency map of adjacent frames shot boundaries are detected. Experiments conducted on videos from TRECVID 2001 and TRECVID 2007 test dataset show that the proposed approach is simple, fast, reliable and robust for shot boundary detection.
AB - Information present in videos are used by variety of applications like surveillance, intelligent business analysis, high tech education etc. To harness this vital information segmenting the video to its basic architectural unit is required. This paper proposes an approach for shot identification based on spectral residual. The spectral residual of a video frame is obtained by analysing the log spectrum of the frame. The ability of spectral residual to represent the innovative or novelty part of the frame and to provide consolidated representation of the scene makes it promising for video segmentation. The spatial domain representation of spectral residual gives the saliency map. At the shot boundaries there will be variations in the innovative regions of the adjacent frames. Using the correlation between the saliency map of adjacent frames shot boundaries are detected. Experiments conducted on videos from TRECVID 2001 and TRECVID 2007 test dataset show that the proposed approach is simple, fast, reliable and robust for shot boundary detection.
UR - http://www.scopus.com/inward/record.url?scp=85007287434&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85007287434&partnerID=8YFLogxK
U2 - 10.1109/ICACCI.2016.7732385
DO - 10.1109/ICACCI.2016.7732385
M3 - Conference contribution
AN - SCOPUS:85007287434
T3 - 2016 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2016
SP - 2242
EP - 2247
BT - 2016 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2016
A2 - Rodrigues, Joel J. P. C.
A2 - Siarry, Patrick
A2 - Perez, Gregorio Martinez
A2 - Tomar, Raghuvir
A2 - Pathan, Al-Sakib Khan
A2 - Mehta, Sameep
A2 - Thampi, Sabu M.
A2 - Berretti, Stefano
A2 - Gorthi, Ravi Prakash
A2 - Pathan, Al-Sakib Khan
A2 - Wu, Jinsong
A2 - Li, Jie
A2 - Jain, Vivek
A2 - Rodrigues, Joel J. P. C.
A2 - Atiquzzaman, Mohammed
A2 - Rodrigues, Joel J. P. C.
A2 - Bedi, Punam
A2 - Kammoun, Mohamed Habib
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Advances in Computing, Communications and Informatics, ICACCI 2016
Y2 - 21 September 2016 through 24 September 2016
ER -