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Graphics and Human Computer Interfaces Commons™
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Articles 871 - 900 of 938
Full-Text Articles in Graphics and Human Computer Interfaces
Image Segmentation Using Multi-Coloured Active Illumination, Tze Ki (Xu Shuqi) Koh, Nicholas Miles, Barrie Hayes-Gill
Image Segmentation Using Multi-Coloured Active Illumination, Tze Ki (Xu Shuqi) Koh, Nicholas Miles, Barrie Hayes-Gill
Research Collection School Of Computing and Information Systems
In this paper, the use of active illumination is extended to image segmentation, specifically in the case of overlapping particles. This work is based on Multi-Flash Imaging (MFI), originally developed by Mitsubishi Electric Labs, to detect depth discontinuities. Illuminations of different wavelengths are projected from multiple positions, providing additional information about a scene compared to conventional segmentation techniques. Shadows are used to identify true object edges. The identification of non- occluded particles is made possible by exploiting the fact that shadows are cast on underlying particles. Implementation issues such as selecting the appropriate colour model and number of illuminations are …
Mining Multiple Visual Appearances Of Semantics For Image Annotation, Hung-Khoon Tan, Chong-Wah Ngo
Mining Multiple Visual Appearances Of Semantics For Image Annotation, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper investigates the problem of learning the visual semantics of keyword categories for automatic image annotation. Supervised learning algorithms which learn only a single concept point of a category are limited in their effectiveness for image annotation. We propose to use data mining techniques to mine multiple concepts, where each concept may consist of one or more visual parts, to capture the diverse visual appearances of a single keyword category. For training, we use the Apriori principle to efficiently mine a set of frequent blobsets to capture the semantics of a rich and diverse visual category. Each concept is …
Introduction: Special Issue For The Selected Papers In The Fourth International Conference On Intelligent Multimedia Computing And Networking (Immcn) 2005, Chong-Wah Ngo, Hong-Va Leong
Introduction: Special Issue For The Selected Papers In The Fourth International Conference On Intelligent Multimedia Computing And Networking (Immcn) 2005, Chong-Wah Ngo, Hong-Va Leong
Research Collection School Of Computing and Information Systems
This special issue introduces seven papers selected from the IMMCN’ 2005, covering a wide range of emerging topics in multimedia field. These papers receive high scores and good comments from the reviewers in their respective areas of intelligent and nextgeneration networking, technology and application, multimedia coding, content analysis and retrieval. The seven papers are extended to 20 pages and then gone through another review process before the final publication. In this issue, we have two papers for video streaming, two papers for multimedia applications, one paper for video coding, and two papers for image and video retrieval.
Modeling Local Interest Points For Semantic Detection And Video Search At Trecvid 2006, Yu-Gang Jiang, Xiaoyong Wei, Chong-Wah Ngo, Hung-Khoon Tan, Wanlei Zhao, Xiao Wu
Modeling Local Interest Points For Semantic Detection And Video Search At Trecvid 2006, Yu-Gang Jiang, Xiaoyong Wei, Chong-Wah Ngo, Hung-Khoon Tan, Wanlei Zhao, Xiao Wu
Research Collection School Of Computing and Information Systems
Local interest points (LIPs) and their features have been shown to obtain surprisingly good results in object detection and recognition. Its effectiveness and scalability, however, have not been seriously addressed in large-scale multimedia database, for instance TRECVID benchmark. The goal of our works is to investigate the role and performance of LIPs, when coupling with multi-modality features, for high-level feature extraction and automatic video search.
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 …
Human-Computer Interaction Research In The Management Information Systems Discipline, Fiona Fui-Hoon Nah, Ping Zhang, Scott Mccoy, Munyong Yi
Human-Computer Interaction Research In The Management Information Systems Discipline, Fiona Fui-Hoon Nah, Ping Zhang, Scott Mccoy, Munyong Yi
Research Collection School Of Computing and Information Systems
No abstract provided.
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 …
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 …
Gestalt-Based Feature Similarity Measure In Trademark Database, Hui Jiang, Chong-Wah Ngo, Hung-Khoon Tan
Gestalt-Based Feature Similarity Measure In Trademark Database, Hui Jiang, Chong-Wah Ngo, Hung-Khoon Tan
Research Collection School Of Computing and Information Systems
Motivated by the studies in Gestalt principle, this paper describes a novel approach on the adaptive selection of visual features for trademark retrieval. We consider five kinds of visual saliencies: symmetry, continuity, proximity, parallelism and closure property. The first saliency is based on Zernike moments, while the others are modeled by geometric elements extracted illusively as a whole from a trademark. Given a query trademark, we adaptively determine the features appropriate for retrieval by investigating its visual saliencies. We show that in most cases, either geometric or symmetric features can give us good enough accuracy. To measure the similarity of …
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 …
Robust Classification Of Eeg Signal For Brain-Computer Interface, Manoj Thulasidas, Cuntai Guan, Jiankang Wu
Robust Classification Of Eeg Signal For Brain-Computer Interface, Manoj Thulasidas, Cuntai Guan, Jiankang Wu
Research Collection School Of Computing and Information Systems
We report the implementation of a text input application (speller) based on the P300 event related potential. We obtain high accuracies by using an SVM classifier and a novel feature. These techniques enable us to maintain fast performance without sacrificing the accuracy, thus making the speller usable in an online mode. In order to further improve the usability, we perform various studies on the data with a view to minimizing the training time required. We present data collected from nine healthy subjects, along with the high accuracies (of the order of 95% or more) measured online. We show that the …
Threading And Autodocumenting News Videos: A Promising Solution To Rapidly Browse News Topics, Xiao Wu, Chong-Wah Ngo, Qing Li
Threading And Autodocumenting News Videos: A Promising Solution To Rapidly Browse News Topics, Xiao Wu, Chong-Wah Ngo, Qing Li
Research Collection School Of Computing and Information Systems
This paper describes the techniques in threading and autodocumenting news stories according to topic themes. Initially, we perform story clustering by exploiting the duality between stories and textual-visual concepts through a co-clustering algorithm. The dependency among stories of a topic is tracked by exploring the textual-visual novelty and redundancy of stories. A novel topic structure that chains the dependencies of stories is then presented to facilitate the fast navigation of the news topic. By pruning the peripheral and redundant news stories in the topic structure, a main thread is extracted for autodocumentary
Exploiting Self-Adaptive Posture-Based Focus Estimation For Lecture Video Editing, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Exploiting Self-Adaptive Posture-Based Focus Estimation For Lecture Video Editing, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Research Collection School Of Computing and Information Systems
Head pose plays a special role in estimating a presenter’s focuses and actions for lecture video editing. This paper presents an efficient and robust head pose estimation algorithm to cope with the new challenges arising in the content management of lecture videos. These challenges include speed requirement, low video quality, variant presenting styles and complex settings in modern classrooms. Our algorithm is based on a robust hierarchical representation of skin color clustering and a set of pose templates that are automatically trained. Contextual information is also considered to refine pose estimation. Most importantly, we propose an online learning approach to …
Selective Object Stabilization For Home Video Consumers, Zailiang Pan, Chong-Wah Ngo
Selective Object Stabilization For Home Video Consumers, Zailiang Pan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper describes a unified approach for video stabilization. The essential goal is to stabilize image sequences that consist of moving foreground objects, which appear frequently in today's home videos captured by hand-held consumer cameras. Our proposed techniques mainly, rely on the analysis of;motion content. Three major components area initialization, segmentation and stabilization. In motion initialization, we propose a novel algorithm to efficiently search for the best possible frame in a sequence to start segmentation. Our segmentation algorithm is based on Expectation-Maximization (EM) framework which provides the mechanism for simultaneous estimation of motion models and their layers of support. Based …
Motion-Based Approach For Bbc Rushes Structuring And Characterization, Chong-Wah Ngo, Zailiang Pan
Motion-Based Approach For Bbc Rushes Structuring And Characterization, Chong-Wah Ngo, Zailiang Pan
Research Collection School Of Computing and Information Systems
No abstract provided.
Common Pattern Discovery Using Earth Mover's Distance And Local Flow Maximization, Hung-Khoon Tan, Chong-Wah Ngo
Common Pattern Discovery Using Earth Mover's Distance And Local Flow Maximization, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
In this paper, we present a novel segmentation-insensitive approach for mining common patterns from 2 images. We develop an algorithm using the earth movers distance (EMD) framework, unary and adaptive neighborhood color similarity. We then propose a novel local flow maximization approach to provide the best estimation of location and scale of the common pattern. This is achieved by performing an iterative optimization in search of the most stable flows' centroid. Common pattern discovery is difficult owing to the huge search space and problem domain. We intend to solve this problem by reducing the search space through identifying the location …
Introduction: Human-Computer Interaction Studies In Management Information Systems, Fiona Fui-Hoon Nah, P. Zhang, S. Mccoy
Introduction: Human-Computer Interaction Studies In Management Information Systems, Fiona Fui-Hoon Nah, P. Zhang, S. Mccoy
Research Collection School Of Computing and Information Systems
Human-computer interaction (HCI) is a critical area of research and practice that spans several disciplines, including industrial engineering, management information systems (MIS), computer science, information science, psychology, sociology, and anthropology. HCI research within the MIS discipline has distinct features shaped by the evolution and current state of MIS. Originating as applied computer science in the 1970s, MIS gradually transformed into a more social science–oriented discipline (Baskerville & Myers, 2002). MIS is broadly defined as “the effective design, delivery, and use of information systems in organizations” (Keen, 1980, p. 14). The two distinguishing features of MIS compared to other "homes" of …
Personalization Of Web Services: A Study On The Fit Between Web Tasks And Personalization Mechanisms, Fiona Fui-Hoon Nah, Keng Siau, Min Ling
Personalization Of Web Services: A Study On The Fit Between Web Tasks And Personalization Mechanisms, Fiona Fui-Hoon Nah, Keng Siau, Min Ling
Research Collection School Of Computing and Information Systems
Personalization is increasingly being considered an important ingredient of Web applications. In most cases, personalization techniques and mechanisms are used for tailoring information services to user needs. It is motivated by the recognition that a user has needs, and meeting them successfully is likely to lead to a satisfying relationship and re-use of the Web services offered. However, if the personalization mechanisms do not match the needs depicted by the tasks, it will decrease user satisfaction and performance. In this research, we use the cognitive fit theory to examine the fit between personalization mechanisms and Web tasks.
End-Users’ Acceptance Of Enterprise Resource Planning Systems: An Investigation Using Grounded Theory Approach, Fiona Fui-Hoon Nah, Xin Tan, Monica Beethe
End-Users’ Acceptance Of Enterprise Resource Planning Systems: An Investigation Using Grounded Theory Approach, Fiona Fui-Hoon Nah, Xin Tan, Monica Beethe
Research Collection School Of Computing and Information Systems
The success of ERP implementation depends, to a large extent, on the intensity and nature of its use by end-users. Therefore, it is important to understand the phenomena underlying end-users’ acceptance of ERP systems. This study was conducted at a large institution that implemented an ERP system. It uses the grounded theory approach to inductively develop a model that highlights key factors influencing end-users’ acceptance of ERP systems.
Emd-Based Video Clip Retrieval By Many-To-Many Matching, Yuxin Peng, Chong-Wah Ngo
Emd-Based Video Clip Retrieval By Many-To-Many Matching, Yuxin Peng, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper presents a new approach for video clip retrieval based on Earth Mover's Distance (EMD). Instead of imposing one-to-one matching constraint as in [11, 14], our approach allows many-to-many matching methodology and is capable of tolerating errors due to video partitioning and various video editing effects. We formulate clip-based retrieval as a graph matching problem in two stages. In the first stage, to allow the matching between a query and a long video, an online clip segmentation algorithm is employed to rapidly locate candidate clips for similarity measure. In the second stage, a weighted graph is constructed to model …
Multibiometrics Based On Palmprint And Handgeometry, Xiao-Yong Wei, Dan Xu, Chong-Wah Ngo
Multibiometrics Based On Palmprint And Handgeometry, Xiao-Yong Wei, Dan Xu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper described our approach of multibiometrics in a single image. Firstly, a new method for capturing the key points of hand geometry is proposed. Then, we described our new method of palmprint feature extracting. By using projection transform and wavelet transform, this method considered both the global feature and local detail of a palmprint texture and proposed a new kind of palmprint feature. We also proposed a twice segmentation method for handgeometry feature extraction. In the processing of feature matching, we analyzed the weakness of the traditional Euclidian Square Norm method, and introduced an improved method. The experimental results …
Co-Clustering Of Time-Evolving News Story With Transcript And Keyframe, Xiao Wu, Chong-Wah Ngo, Qing Li
Co-Clustering Of Time-Evolving News Story With Transcript And Keyframe, Xiao Wu, Chong-Wah Ngo, Qing Li
Research Collection School Of Computing and Information Systems
This paper presents techniques in clustering the same-topic news stories according to event themes. We model the relationship of stories with textual and visual concepts under the representation of bipartite graph. The textual and visual concepts are extracted respectively from speech transcripts and keyframes. Co-clustering algorithm is employed to exploit the duality of stories and textual-visual concepts based on spectral graph partitioning. Experimental results on TRECVID-2004 corpus show that the co-clustering of news stories with textual-visual concepts is significantly better than the co-clustering with either textual or visual concept alone.
Hot Event Detection And Summarization By Graph Modeling And Matching, Yuxin Peng, Chong-Wah Ngo
Hot Event Detection And Summarization By Graph Modeling And Matching, Yuxin Peng, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper proposes a new approach for hot event detection and summarization of news videos. The approach is mainly based on two graph algorithms: optimal matching (OM) and normalized cut (NC). Initially, OM is employed to measure the visual similarity between all pairs of events under the one-to-one mapping constraint among video shots. Then, news events are represented as a complete weighted graph and NC is carried out to globally and optimally partition the graph into event clusters. Finally, based on the cluster size and globality of events, hot events can be automatically detected and selected as the summaries of …
Video Text Detection And Segmentation For Optical Character Recognition, Chong-Wah Ngo, Chi-Kwong Chan
Video Text Detection And Segmentation For Optical Character Recognition, Chong-Wah Ngo, Chi-Kwong Chan
Research Collection School Of Computing and Information Systems
In this paper, we present approaches to detecting and segmenting text in videos. The proposed video-text-detection technique is capable of adaptively applying appropriate operators for video frames of different modalities by classifying the background complexities. Effective operators such as the repeated shifting operations are applied for the noise removal of images with high edge density. Meanwhile, a text-enhancement technique is used to highlight the text regions of low-contrast images. A coarse-to-fine projection technique is then employed to extract text lines from video frames. Experimental results indicate that the proposed text-detection approach is superior to the machine-learning-based (such as SVM and …
Video Summarization And Scene Detection By Graph Modeling, Chong-Wah Ngo, Yu-Fei Ma, Hong-Jiang Zhang
Video Summarization And Scene Detection By Graph Modeling, Chong-Wah Ngo, Yu-Fei Ma, Hong-Jiang Zhang
Research Collection School Of Computing and Information Systems
In this paper, we propose a unified approach for video summarization based on the analysis of video structures and video highlights. Two major components in our approach are scene modeling and highlight detection. Scene modeling is achieved by normalized cut algorithm and temporal graph analysis, while highlight detection is accomplished by motion attention modeling. In our proposed approach, a video is represented as a complete undirected graph and the normalized cut algorithm is carried out to globally and optimally partition the graph into video clusters. The resulting clusters form a directed temporal graph and a shortest path algorithm is proposed …
Special Section: Human-Computer Interaction Research In Management Information Systems, Ping Zhang, Fiona Fui-Hoon Nah, Izak Benbasat
Special Section: Human-Computer Interaction Research In Management Information Systems, Ping Zhang, Fiona Fui-Hoon Nah, Izak Benbasat
Research Collection School Of Computing and Information Systems
No abstract provided.
High Performance P300 Speller For Brain-Computer Interface, Cuntai Guan, Manoj Thulasidas, Jiankang Wu
High Performance P300 Speller For Brain-Computer Interface, Cuntai Guan, Manoj Thulasidas, Jiankang Wu
Research Collection School Of Computing and Information Systems
P300 speller is a communication tool with which one can input texts or commands to a computer by thought. The amplitude of the P300 evoked potential is inversely proportional to the probability of infrequent or task-related stimulus. In existing P300 spellers, rows and columns of a matrix are intensified successively and randomly, resulting in a stimulus frequency of 1/N (N is the number of rows or columns of the matrix). We propose a new paradigm to display each single character randomly and individually (therefore reducing the stimulus frequency to 1/(N*N)). On-line experiments showed that this new speller significantly improved the …
Indexing And Matching Of Polyphonic Songs For Query-By-Singing System, Tat-Wan Leung, Chong-Wah Ngo
Indexing And Matching Of Polyphonic Songs For Query-By-Singing System, Tat-Wan Leung, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper investigates the issues in polyphonic popular song retrieval. The problems that we consider include singing voice extraction, melodic curve representation, and database indexing. Initially, polyphonic songs are decomposed into singing voices and instruments sounds in both time and frequency domains based on SVM and ICA. The extracted singing voices are represented as two melodic curves that model the statistical mean and neighborhood similarity of notes. To speed up the matching between songs and query, we further adopt proportional transportation distance to index the songs as vantage point trees. Encouraging results have been obtained through experiments.