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- Background Clutter (1)
- Clip similarity (1)
- Color Histogram (1)
- Document summarization (1)
- Hierarchical Hidden Markov Model (1)
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- Hierarchical video retrieval (1)
- Keyframe tracking (1)
- Keypoint matching (1)
- Linear Mixture Model (1)
- Locality Sensitive Hash (1)
- Maximal Stable Extreme Region (1)
- Metadata (1)
- Motion pictures (1)
- Near-duplicate detection (1)
- Pattern entropy (1)
- Query-based segmentation (1)
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- Text segment (1)
- Textual feature (1)
- Transitivity propagation (1)
- Video Search (1)
Articles 1 - 6 of 6
Full-Text Articles in Databases and Information Systems
Fast Tracking Of Near-Duplicate Keyframes In Broadcast Domain With Transitivity Propagation, Chong-Wah Ngo, Wan-Lei Zhao, Yu-Gang Jiang
Fast Tracking Of Near-Duplicate Keyframes In Broadcast Domain With Transitivity Propagation, Chong-Wah Ngo, Wan-Lei Zhao, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
The identification of near-duplicate keyframe (NDK) pairs is a useful task for a variety of applications such as news story threading and content-based video search. In this paper, we propose a novel approach for the discovery and tracking of NDK pairs and threads in the broadcast domain. The detection of NDKs in a large data set is a challenging task due to the fact that when the data set increases linearly, the computational cost increases in a quadratic speed, and so does the number of false alarms. This paper explores the symmetric and transitive nature of near-duplicate for the effective …
Discovering Image-Text Associations For Cross-Media Web Information Fusion, Tao Jiang, Ah-Hwee Tan
Discovering Image-Text Associations For Cross-Media Web Information Fusion, Tao Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
The diverse and distributed nature of the information published on the World Wide Web has made it difficult to collate and track information related to specific topics. Whereas most existing work on web information fusion has focused on multiple document summarization, this paper presents a novel approach for discovering associations between images and text segments, which subsequently can be used to support cross-media web content summarization. Specifically, we employ a similarity-based multilingual retrieval model and adopt a vague transformation technique for measuring the information similarity between visual features and textual features. The experimental results on a terrorist domain document set …
Hierarchical Hidden Markov Model For Rushes Structuring And Indexing, Chong-Wah Ngo, Zailiang Pan, Xiaoyong Wei
Hierarchical Hidden Markov Model For Rushes Structuring And Indexing, Chong-Wah Ngo, Zailiang Pan, Xiaoyong Wei
Research Collection School Of Computing and Information Systems
Rushes footage are considered as cheap gold mine with the potential for reuse in broadcasting and filmmaking industries. However, it is difficult to mine the "gold" from the rushes since usually only minimum metadata is available. This paper focuses on the structuring and indexing of the rushes to facilitate mining and retrieval of "gold". We present a new approach for rushes structuring and indexing based on motion feature. We model the problem by a two-level Hierarchical Hidden Markov Model (HHMM). The HHMM, on one hand, represents the semantic concepts in its higher level to provide simultaneous structuring and indexing, on …
Prediction-Based Gesture Detection In Lecture Videos By Combining Visual, Speech And Electronic Slides, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Prediction-Based Gesture Detection In Lecture Videos By Combining Visual, Speech And Electronic Slides, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Research Collection School Of Computing and Information Systems
This paper presents an efficient algorithm for gesture detection in lecture videos by combining visual, speech and electronic slides. Besides accuracy, response time is also considered to cope with the efficiency requirements of real-time applications. Candidate gestures are first detected by visual cue. Then we modifity HMM models for complete gestures to predict and recognize incomplete gestures before the whole gestures paths are observed. Gesture recognition is used to verify the results of gesture detection. The relations between visual, speech and slides are analyzed. The correspondence between speech and gesture is employed to improve the accuracy and the responsiveness of …
Keyframe Retrieval By Keypoints: Can Point-To-Point Matching Help?, Wanlei Zhao, Yu-Gang Jiang, Chong-Wah Ngo
Keyframe Retrieval By Keypoints: Can Point-To-Point Matching Help?, Wanlei Zhao, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Bag-of-words representation with visual keypoints has recently emerged as an attractive approach for video search. In this paper, we study the degree of improvement when point-to-point (P2P) constraint is imposed on the bag-of-words. We conduct investigation on two tasks: near-duplicate keyframe (NDK) retrieval, and high-level concept classification, covering parts of TRECVID 2003 and 2005 datasets. In P2P matching, we propose a one-to-one symmetric keypoint matching strategy to diminish the noise effect during keyframe comparison. In addition, a new multi-dimensional index structure is proposed to speed up the matching process with keypoint filtering. Through experiments, we demonstrate that P2P constraint can …
Clip-Based Similarity Measure For Query-Dependent Clip Retrieval And Video Summarization, Yuxin Peng, Chong-Wah Ngo
Clip-Based Similarity Measure For Query-Dependent Clip Retrieval And Video Summarization, Yuxin Peng, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper proposes a new approach and algorithm for the similarity measure of video clips. The similarity is mainly based on two bipartite graph matching algorithms: maximum matching (MM) and optimal matching (OM). MM is able to rapidly filter irrelevant video clips, while OM is capable of ranking the similarity of clips according to visual and granularity factors. We apply the similarity measure for two tasks: retrieval and summarization. In video retrieval, a hierarchical retrieval framework is constructed based on MM and OM. The validity of the framework is theoretically proved and empirically verified on a video database of 21 …