Key-Lectures: Keyframes Extraction in Video Lectures
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Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-13-0923-6_39
Reference7 articles.
1. 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. 1039–1048 (2016)
2. Sun, M., Farhadi, A., Taskar, B., Seitz, S.: Summarizing unconstrained videos using salient montages. IEEE Trans. Pattern Anal. Mach. Intell. 39(11), 2256–2269 (2017)
3. Cirne, M.V.M., Pedrini, H.: VISCOM: a robust video summarization approach using color co-occurrence matrices. Multimed. Tools Appl. 1–19 (2017)
4. Mishra, D.K., Singh, N.: Parameter free clustering approach for event summarization in videos. In: Proceedings of International Conference on Computer Vision and Image Processing, pp. 389–397. Springer, Singapore (2017)
5. Kumar, K., Shrimankar, D.D., Singh, N.: Equal partition based clustering approach for event summarization in videos. In: 12th International Conference on Signal-Image Technology and Internet-Based Systems (SITIS), pp. 119–126. IEEE (2016)
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