Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
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.
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
The Hydra Filesystem: A Distrbuted Storage Famework, Benjamin Gonzalez, George K. Thiruvathukal
The Hydra Filesystem: A Distrbuted Storage Famework, Benjamin Gonzalez, George K. Thiruvathukal
Computer Science: Faculty Publications and Other Works
Hydra File System (HFS) is an experimental framework for constructing parallel and distributed filesystems. While parallel and distributed applications requiring scalable and flexible access to storage and retrieval are becoming more commonplace, parallel and distributed filesystems remain difficult to deploy easily and configure for different needs. HFS aims to be different by being true to the tradition of high-performance computing while employing modern design patterns to allow various policies to be configured on a per instance basis (e.g. storage, communication, security, and indexing schemes). We describe a working prototype (available for public download) that has been implemented in the Python …