Object hyperlinking

Abstract: Massive amounts of digital media is being produced and consumed daily on the Internet. Efficient access to relevant information is of key importance in contemporary society. The Hyper Video Browser provides multiple navigation means within the content of a media repository. Our system utilizes the state of the art multimodal content analysis and indexing techniques, at multiple temporal granularity, in order to satisfy the user need by suggesting relevant material. We integrate two intuitive interfaces: for search and browsing through the video archive, and for further hyperlinking to the related content while enjoying some video content. The novelty of this work includes a multi-faceted search and browsing interface for navigating in video collections and the dynamic suggestion of hyperlinks related to a media fragment content, rather than the entire video, being viewed. The approach was evaluated on the MediaEval Search and Hyperlinking task, demonstrating its effectiveness at locating accurately relevant content in a big media archive.

Abstract: In this paper, we address the problem of object retrieval by hyperlinking the reference data set at subimage level. One of the main challenges in object retrieval involves small objects on cluttered backgrounds, where the similarity between the querying object and a relevant image can be heavily affected by the background. To address this problem, we propose an efficient object retrieval technique by hyperlinking the visual entities among the reference data set. In particular, a two-step framework is proposed: subimage-level hyperlinking and hyperlink-aware reranking. For hyperlinking, we propose a scalable object mining technique using Thread-of-Features, which is designed for mining subimage-level objects. For reranking, the initial search results are reranked with a hyperlink-aware transition matrix encoding subimage-level connectivity. Through this framework, small objects can be retrieved effectively. Moreover, our method introduces only a tiny computation overhead to online processing, due to the sparse transition matrix. The proposed technique is featured by the novel perspective (object hyperlinking) for visual search, as well as the object hyperlinking technique. We demonstrate the effectiveness and efficiency of our hyperlinking and retrieval methods by experimenting upon several object-retrieval data sets.

Abstract: Showing video and article on the same page, as done by official web agencies such as CNN.com and Yahoo!, provides a practical way for convenient information digestion. However, as the absence of article, this layout is infeasible for mainstream web video repositories like YouTube. This paper investigates the problem of hyperlinking web videos to relevant articles available on the Web. Given a video, the task is accomplished by firstly identifying its contextual tags (e.g., who are doing what at where and when) and then employing a search based association to relevant articles. Specifically, we propose a multiple tag property exploration (mTagPE) approach to identify contextual tags, where tag relevance, tag clarity and tag correlation are defined and measured by leveraging visual duplicate analyses, online knowledge bases and tag co-occurrence. Then, the identification task is formulated as a random walk along a tag relation graph that smoothly integrates the three properties. The random walk aims at picking up relevant, clear and correlated tags as a set of contextual tags, which is further treated as a query to issue commercial search engines to obtain relevant articles. We have conducted experiments on a largescale web video dataset. Both objective performance evaluations and subjective user studies show the effectiveness of the proposed hyperlinking. It produces more accurate contextual tags and thus a larger number of relevant articles than other approaches.

Abstract: A communications network connects a plurality of objects. The objects include a real physical world object, a virtual world object representing the real physical world object, and a model world object representing the real physical world object. The network connects the objects to reflect a change of state in any one object in any of the other objects.