{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T10:07:07Z","timestamp":1779358027148,"version":"3.51.4"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T00:00:00Z","timestamp":1601942400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T00:00:00Z","timestamp":1601942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100002889","name":"Cochin University of Science and Technology","doi-asserted-by":"publisher","award":["PL.(UGC)1\/SPG\/SMNRI\/2018-19"],"award-info":[{"award-number":["PL.(UGC)1\/SPG\/SMNRI\/2018-19"]}],"id":[{"id":"10.13039\/501100002889","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2021,6]]},"DOI":"10.1007\/s11760-020-01791-4","type":"journal-article","created":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T23:03:58Z","timestamp":1602025438000},"page":"735-742","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Static video summarization using multi-CNN with sparse autoencoder and random forest classifier"],"prefix":"10.1007","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6039-5727","authenticated-orcid":false,"given":"Madhu S.","family":"Nair","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jesna","family":"Mohan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,6]]},"reference":[{"issue":"1","key":"1791_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1198302.1198303","volume":"3","author":"BT Truong","year":"2007","unstructured":"Truong, B.T., Venkatesh, S.: Video abstraction: a systematic review and classification. ACM Trans. Multimed. Comput. Commun. Appl. (TOMM) 3(1), 1\u201337 (2007)","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl. (TOMM)"},{"issue":"1","key":"1791_CR2","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/s11042-009-0307-7","volume":"46","author":"M Furini","year":"2010","unstructured":"Furini, M., Geraci, F., Montangero, M., Pellegrini, M.: Stimo: still and moving video storyboard for the web scenario. Multimed. Tools Appl. 46(1), 47\u201369 (2010)","journal-title":"Multimed. Tools Appl."},{"key":"1791_CR3","doi-asserted-by":"crossref","unstructured":"Gygli, M., Grabner, H., Riemenschneider, H., Van\u00a0Gool, L.: Creating summaries from user videos. In: European Conference on Computer Vision, pp. 505\u2013520. Springer (2014)","DOI":"10.1007\/978-3-319-10584-0_33"},{"issue":"6","key":"1791_CR4","doi-asserted-by":"publisher","first-page":"1049","DOI":"10.1016\/S0165-1684(00)00019-0","volume":"80","author":"AD Doulamis","year":"2000","unstructured":"Doulamis, A.D., Doulamis, N.D., Kollias, S.D.: A fuzzy video content representation for video summarization and content-based retrieval. Sig. Process. 80(6), 1049\u20131067 (2000)","journal-title":"Sig. Process."},{"issue":"4","key":"1791_CR5","doi-asserted-by":"publisher","first-page":"729","DOI":"10.1109\/TCSVT.2012.2214871","volume":"23","author":"G Guan","year":"2013","unstructured":"Guan, G., Wang, Z., Lu, S., Da Deng, J., Feng, D.D.: Keypoint-based keyframe selection. IEEE Trans. Circuits Syst. Video Technol. 23(4), 729\u2013734 (2013)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"2","key":"1791_CR6","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1007\/s13735-016-0095-6","volume":"5","author":"R Hannane","year":"2016","unstructured":"Hannane, R., Elboushaki, A., Afdel, K., Naghabhushan, P., Javed, M.: An efficient method for video shot boundary detection and keyframe extraction using sift-point distribution histogram. Int. J. Multimed. Inf. Retriev. 5(2), 89\u2013104 (2016)","journal-title":"Int. J. Multimed. Inf. Retriev."},{"key":"1791_CR7","doi-asserted-by":"publisher","first-page":"102685","DOI":"10.1016\/j.jvcir.2019.102685","volume":"65","author":"Y Chen","year":"2019","unstructured":"Chen, Y., Hu, R., Xiao, J., Wang, Z.: Multisource surveillance video coding with synthetic reference frame. J. Vis. Commun. Image Represent. 65, 102685 (2019)","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"11","key":"1791_CR8","doi-asserted-by":"publisher","first-page":"5469","DOI":"10.1109\/TIP.2016.2601493","volume":"25","author":"S Zhang","year":"2016","unstructured":"Zhang, S., Zhu, Y., Roy-Chowdhury, A.K.: Context-aware surveillance video summarization. IEEE Trans. Image Process. 25(11), 5469\u20135478 (2016)","journal-title":"IEEE Trans. Image Process."},{"key":"1791_CR9","doi-asserted-by":"crossref","unstructured":"Mahasseni, B., Lam, M., Todorovic, S.: Unsupervised video summarization with adversarial lstm networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (2017)","DOI":"10.1109\/CVPR.2017.318"},{"issue":"1","key":"1791_CR10","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1109\/TII.2019.2929228","volume":"16","author":"T Hussain","year":"2019","unstructured":"Hussain, T., Muhammad, K., Ullah, A., Cao, Z., Baik, S.W., de Albuquerque, V.H.C.: Cloud-assisted multiview video summarization using cnn and bidirectional lstm. IEEE Trans. Ind. Inf. 16(1), 77\u201386 (2019)","journal-title":"IEEE Trans. Ind. Inf."},{"key":"1791_CR11","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1016\/j.jvcir.2016.12.001","volume":"42","author":"M Fei","year":"2017","unstructured":"Fei, M., Jiang, W., Mao, W.: Memorable and rich video summarization. J. Vis. Commun. Image Represent. 42, 207\u2013217 (2017)","journal-title":"J. Vis. Commun. Image Represent."},{"key":"1791_CR12","doi-asserted-by":"crossref","unstructured":"Rochan, M., Ye, L., Wang, Y.: Video summarization using fully convolutional sequence networks. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 347\u2013363 (2018)","DOI":"10.1007\/978-3-030-01258-8_22"},{"issue":"2","key":"1791_CR13","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1109\/TMM.2008.2009703","volume":"11","author":"B-W Chen","year":"2009","unstructured":"Chen, B.-W., Wang, J.-C., Wang, J.-F.: A novel video summarization based on mining the story-structure and semantic relations among concept entities. IEEE Trans. Multimed. 11(2), 295\u2013312 (2009)","journal-title":"IEEE Trans. Multimed."},{"key":"1791_CR14","doi-asserted-by":"crossref","unstructured":"Meng, J., Wang, H., Yuan, J., Tan, Y.-P.: From keyframes to key objects: video summarization by representative object proposal selection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1039\u20131048 (2016)","DOI":"10.1109\/CVPR.2016.118"},{"issue":"8","key":"1791_CR15","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1109\/TMM.2010.2058795","volume":"12","author":"N Shroff","year":"2010","unstructured":"Shroff, N., Turaga, P., Chellappa, R.: Video pr\u00e9cis: highlighting diverse aspects of videos. IEEE Trans. Multimed. 12(8), 853\u2013868 (2010)","journal-title":"IEEE Trans. Multimed."},{"key":"1791_CR16","doi-asserted-by":"crossref","unstructured":"Gygli, M., Grabner, H., Van\u00a0Gool, L.: Video summarization by learning submodular mixtures of objectives. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3090\u20133098 (2015)","DOI":"10.1109\/CVPR.2015.7298928"},{"key":"1791_CR17","doi-asserted-by":"crossref","unstructured":"Taj-Eddin, I.A., Afifi, M., Korashy, M., Hamdy, D., Nasser, M., Derbaz, S.: A new compression technique for surveillance videos: evaluation using new dataset. In: 2016 Sixth International Conference on Digital Information and Communication Technology and its Applications (DICTAP), pp. 159\u2013164. IEEE (2016)","DOI":"10.1109\/DICTAP.2016.7544020"},{"key":"1791_CR18","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1016\/j.patrec.2018.08.003","volume":"130","author":"K Muhammad","year":"2020","unstructured":"Muhammad, K., Hussain, T., Baik, S.W.: Efficient cnn based summarization of surveillance videos for resource-constrained devices. Pattern Recogn. Lett. 130, 370\u2013375 (2020)","journal-title":"Pattern Recogn. Lett."},{"key":"1791_CR19","doi-asserted-by":"crossref","unstructured":"Nair, M.S., Mohan, J.: Video summarization using convolutional neural network and random forest classifier. In: TENCON 2019\u20132019 IEEE Region 10 Conference (TENCON), pp. 476\u2013480. IEEE (2019)","DOI":"10.1109\/TENCON.2019.8929724"},{"key":"1791_CR20","doi-asserted-by":"crossref","unstructured":"Liu, C., Yuen, J., Torralba, A., Sivic, J., Freeman, W.T.: Sift flow: dense correspondence across different scenes. In: European Conference on Computer Vision, pp. 28\u201342. Springer (2008)","DOI":"10.1007\/978-3-540-88690-7_3"},{"issue":"10","key":"1791_CR21","doi-asserted-by":"publisher","first-page":"e02699","DOI":"10.1016\/j.heliyon.2019.e02699","volume":"5","author":"J Mohan","year":"2019","unstructured":"Mohan, J., Nair, M.S.: Domain independent redundancy elimination based on flow vectors for static video summarization. Heliyon 5(10), e02699 (2019)","journal-title":"Heliyon"},{"issue":"2","key":"1791_CR22","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91\u2013110 (2004)","journal-title":"Int. J. Comput. Vis."},{"issue":"1","key":"1791_CR23","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/s11263-006-7899-4","volume":"70","author":"PF Felzenszwalb","year":"2006","unstructured":"Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient belief propagation for early vision. Int. J. Comput. Vis. 70(1), 41\u201354 (2006)","journal-title":"Int. J. Comput. Vis."},{"issue":"7553","key":"1791_CR24","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436 (2015)","journal-title":"Nature"},{"key":"1791_CR25","unstructured":"LeCun, Y., Boser, B.E., Denker, J.S., Henderson, D., Howard, R.E., Hubbard, W.E., Jackel, L.D.: Handwritten digit recognition with a back-propagation network. In: Advances in Neural Information Processing Systems, pp. 396\u2013404 (1990)"},{"issue":"1","key":"1791_CR26","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929\u20131958 (2014)","journal-title":"J. Mach. Learn. Res."},{"key":"1791_CR27","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich A., et\u00a0al.: Going deeper with convolutions. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"1791_CR28","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556 (2014)"},{"key":"1791_CR29","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Ioffe, S., Vanhoucke, V., Alemi, A.A.: Inception-v4, inception-resnet and the impact of residual connections on learning. In: Thirty-First AAAI Conference on Artificial Intelligence (2017)","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"1791_CR30","unstructured":"Coates, A., Ng, A., Lee, H.: An analysis of single-layer networks in unsupervised feature learning. In: Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, pp. 215\u2013223 (2011)"},{"issue":"1","key":"1791_CR31","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"issue":"1","key":"1791_CR32","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.patrec.2010.08.004","volume":"32","author":"SEF De Avila","year":"2011","unstructured":"De Avila, S.E.F., Lopes, A.P.B., da Luz, A., de Albuquerque Ara\u00fajo, A.: Vsumm: a mechanism designed to produce static video summaries and a novel evaluation method. Pattern Recognit. Lett. 32(1), 56\u201368 (2011)","journal-title":"Pattern Recognit. Lett."},{"issue":"260","key":"1791_CR33","first-page":"1","volume":"76","author":"J Wu","year":"2016","unstructured":"Wu, J., Zhong, S.-H., Jiang, J., Yang, Y.: A novel clustering method for static video summarization. Multimed. Tools Appl. 76(260), 1\u201317 (2016)","journal-title":"Multimed. Tools Appl."},{"issue":"1","key":"1791_CR34","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1007\/s11042-016-4300-7","volume":"77","author":"MVM Cirne","year":"2018","unstructured":"Cirne, M.V.M., Pedrini, H.: Viscom: a robust video summarization approach using color co-occurrence matrices. Multimed. Tools Appl. 77(1), 857\u2013875 (2018)","journal-title":"Multimed. Tools Appl."},{"key":"1791_CR35","doi-asserted-by":"crossref","unstructured":"de Avila, S. E., da Luz Jr, A., Ara\u00fajo, A. D. A., Cord, M.: Vsumm: An approach for automatic video summarization and quantitative evaluation. In: XXI Brazilian Symposium on Computer Graphics and Image Processing: SIBGRAPI\u201908. IEEE 2008, pp. 103\u2013110 (2008)","DOI":"10.1109\/SIBGRAPI.2008.31"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-020-01791-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-020-01791-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-020-01791-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T09:53:17Z","timestamp":1669110797000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-020-01791-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,6]]},"references-count":35,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,6]]}},"alternative-id":["1791"],"URL":"https:\/\/doi.org\/10.1007\/s11760-020-01791-4","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,6]]},"assertion":[{"value":"18 May 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 August 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 September 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 October 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}