Semantic Indexing of Large Scale Video Archives
Project Member(s): Yang, Y.
Funding or Partner Organisation: D2D CRC LTD
Start year: 2015
Summary: Identifying semantic content in Internet videos has long been a goal of multimedia analysis and retrieval, and has broad impact on many real world applications, ranging from our daily life to security. This fundamental problem is also a building block for many tasks such as visualization, abstraction, recommendation, retrieval and summarization of videos. As opposed to merely using user-generated metadata, such as titles and descriptions, content-based semantic indexing strives to leverage concepts that are automatically detected in the video, such as objects/scenes/actions. This semantic indexing relies on extensive video understanding, and requires neither metadata nor example videos. The outcome of this project will provide us hassle free analytical tools for big video data management and utilization. The output of our system can also be feed into other text data mining platforms to enrich the type of data source for powerful multi-source multi-modality data mining at large scale.
Publications:
Nie, L, Wei, X, Zhang, D, Wang, X, Gao, Z & Yang, Y 2017, 'Data-Driven Answer Selection in Community QA Systems', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 6, pp. 1186-1198.
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Yan, Y, Yang, T, Yang, Y & Chen, J 1970, 'A framework of online learning with imbalanced streaming data', 31st AAAI Conference on Artificial Intelligence, AAAI 2017, AAAI Conference on Artificial Intelligence, AAAI, San Francisco, USA, pp. 2817-2823.
Gan, C, Yang, Y, Zhu, L, Zhao, D & Zhuang, Y 2016, 'Recognizing an Action Using Its Name: A Knowledge-Based Approach', International Journal of Computer Vision, vol. 120, no. 1, pp. 61-77.
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Chang, X, Yu, Y-L, Yang, Y & Xing, EP 1970, 'They are Not Equally Reliable: Semantic Event Search Using Differentiated Concept Classifiers', 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, Las Vegas, Nevada, United States, pp. 1884-1893.
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Pan, P, Xu, Z, Yang, Y, Wu, F & Zhuang, Y 1970, 'Hierarchical Recurrent Neural Encoder for Video Representation with Application to Captioning', Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Seattle, WA, USA, pp. 1029-1038.
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Chang, X, Nie, F, Yang, Y & Huang, H 2014, 'A Convex Sparse PCA for Feature Analysis', ACM Transactions on Knowledge Discovery from Data, vol. 11, no. 1, pp. 1-16.
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Chang, X, Nie, F, Yang, Y & Huang, H 2014, 'Improved Spectral Clustering via Embedded Label Propagation'.
Keywords: Video Analysis, Semantic Indexing, Computer Vision, Multimedia
FOR Codes: Artificial Intelligence and Image Processing, Pattern Recognition and Data Mining, Multimedia Programming, Information Processing Services (incl. Data Entry and Capture), Application Tools and System Utilities, Electronic Information Storage and Retrieval Services, Computer vision and multimedia computation not elsewhere classified, Data mining and knowledge discovery, Computer vision and multimedia computation, Information systems, technologies and services not elsewhere classified