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- Keyword
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- Video browsing (2)
- Concept-driven fusion (1)
- Event extraction (1)
- Graph fusion (1)
- Heterogeneous modality fusion (1)
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- Information visualization (1)
- Media content synchronization (1)
- Modality agreement (1)
- Multi-modality (1)
- Re-ranking (1)
- Semantic concept (1)
- Semantic pooling; Training set construction; Visual concepts (1)
- Summarization (1)
- Topic trajectory mining (1)
- Video recommendation (1)
- Video search (1)
- Visual summarization (1)
- Visualization (1)
Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
Cross Media Hyperlinking For Search Topic Browsing, Song Tan, Chong-Wah Ngo, Hung-Khoon Tan, Lei Pang
Cross Media Hyperlinking For Search Topic Browsing, Song Tan, Chong-Wah Ngo, Hung-Khoon Tan, Lei Pang
Research Collection School Of Computing and Information Systems
With the rapid growth of social media, there are plenty of information sources freely available online for use. Nevertheless, how to synchronize and leverage these diverse forms of information for multimedia applications remains a problem yet to be seriously studied. This paper investigates the synchronization of multiple media content in the physical form of hyperlinking them. The ultimate goal is to develop browsing systems that author search results with rich media information mined from various knowledge sources. The authoring enables the vivid visualization and exploration of different information landscapes inherent in search results. Several key techniques are studied in this …
On The Pooling Of Positive Examples With Ontology For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang
On The Pooling Of Positive Examples With Ontology For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
A common obstacle in effective learning of visual concept classifiers is the scarcity of positive training examples due to expensive labeling cost. This paper explores the sampling of weakly tagged web images for concept learning without human assistance. In particular, ontology knowledge is incorporated for semantic pooling of positive examples from ontologically neighboring concepts. This effectively widens the coverage of the positive samples with visually more diversified content, which is important for learning a good concept classifier. We experiment with two learning strategies: aggregate and incremental. The former strategy re-trains a new classifier by combining existing and newly collected examples, …
Tracking Web Video Topics: Discovery, Visualization, And Monitoring, Juan Cao, Chong-Wah Ngo, Yong-Dong Zhang, Jin-Tao Li
Tracking Web Video Topics: Discovery, Visualization, And Monitoring, Juan Cao, Chong-Wah Ngo, Yong-Dong Zhang, Jin-Tao Li
Research Collection School Of Computing and Information Systems
Despite the massive growth of web-shared videos in Internet, efficient organization and monitoring of videos remains a practical challenge. While nowadays broadcasting channels are keen to monitor online events, identifying topics of interest from huge volume of user uploaded videos and giving recommendation to emerging topics are by no means easy. Specifically, such process involves discovering of new topic, visualization of the topic content, and incremental monitoring of topic evolution. This paper studies the problem from three aspects. First, given a large set of videos collected over months, an efficient algorithm based on salient trajectory extraction on a topic evolution …
Galaxy Browser: Exploratory Search Of Web Videos, Lei Pang, Song Tan, Hung-Khoon Tan, Chong-Wah Ngo
Galaxy Browser: Exploratory Search Of Web Videos, Lei Pang, Song Tan, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Most search engines return a ranked list of items in response to a query. The list however tells very little about the relationship among items. For videos especially, users often read to spend significant amount of time to navigate the search result. Exploratory search presents a new paradigm for browsing where the browser takes up the role of information exploring and presents a well-organized browsing structure for users to navigate. The proposed interface Galaxy Browser adopts the recent advances in near-duplicate detection and then synchronizes the detected near-duplicate information with comprehensive background knowledge derived from online external resources. The result …
Fusing Heterogeneous Modalities For Video And Image Re-Ranking, Hung-Khoon Tan, Chong-Wah Ngo
Fusing Heterogeneous Modalities For Video And Image Re-Ranking, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Multimedia documents in popular image and video sharing websites such as Flickr and Youtube are heterogeneous documents with diverse ways of representations and rich user-supplied information. In this paper, we investigate how the agreement among heterogeneous modalities can be exploited to guide data fusion. The problem of fusion is cast as the simultaneous mining of agreement from different modalities and adaptation of fusion weights to construct a fused graph from these modalities. An iterative framework based on agreement-fusion optimization is thus proposed. We plug in two well-known algorithms: random walk and semi-supervised learning to this framework to illustrate the idea …
Mining Event Structures From Web Videos, Xiao Wu, Yi-Jie Lu, Qiang Peng, Chong-Wah Ngo
Mining Event Structures From Web Videos, Xiao Wu, Yi-Jie Lu, Qiang Peng, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The article is discussing the issues of mining event structures from Web video search results using text analysis, burst detection, and clustering as with the proliferation of social media, the volume of Web videos have grown exponentially.
Concept-Driven Multi-Modality Fusion For Video Search, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo
Concept-Driven Multi-Modality Fusion For Video Search, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
As it is true for human perception that we gather information from different sources in natural and multi-modality forms, learning from multi-modalities has become an effective scheme for various information retrieval problems. In this paper, we propose a novel multi-modality fusion approach for video search, where the search modalities are derived from a diverse set of knowledge sources, such as text transcript from speech recognition, low-level visual features from video frames, and high-level semantic visual concepts from supervised learning. Since the effectiveness of each search modality greatly depends on specific user queries, prompt determination of the importance of a modality …