In this technical demonstration, we showcase a multimedia search engine that facilitates semantic access to archival rock n' roll concert video. The key novelty is the crowdsourcing mechanism, which relies on online users to improve, extend, and share, automatically detected results in video fragments using an advanced timeline-based video player. The user-feedback serves as valuable input to further improve automated multimedia retrieval results, such as automatically detected concepts and automatically transcribed interviews. The search engine has been operational online to harvest valuable feedback from rock n' roll enthusiasts.

In this video demonstration, we advertise the MediaMill video search engine, a system that facilitates semantic access to video based on a large lexicon of visual concept detectors and interactive video browsers. With an ultimate aim to disseminate video retrieval research to a non-technical audience, we explain the need for a visual video retrieval solution, summarize the MediaMill technology, and hint at future perspectives.

In this technical demonstration we showcase the MediaMill Semantic Video Search Engine. It allows usage of multiple query methods embedded into a single browsing environment while guiding the user to better results by using a novel active learning strategy. This allows for fast and effective search trough large video collections.

In this technical demonstration we showcase the MediaMill ForkBrowser for video retrieval. It embeds multiple query methods into a single browsing environment. We show that users can switch query methods on demand without the need to adapt to a different interface. This allows for fast and effective search trough large video collections.

In this demonstration we showcase an interactive analysis tool for researchers working on concept-based video retrieval. By visualizing intermediate concept detection analysis stages, the tool aids in understanding the success and failure of video concept detection methods. We demonstrate the tool on the domain of pop concert video.

In this technical demonstration we showcase the current version of the MediaMill system, a search engine that facilitates access to news video archives at a semantic level. The core of the system is a thesaurus of 500 automatically detected semantic concepts. To handle such a large thesaurus in retrieval, an engine is developed which automatically selects a set of relevant concepts based on a textual query, and an novel user interface which uses multi dimensional browsing to visualize the result set.

In this technical demonstration we showcase the RotorBrowser, A visualization within MediaMill system which uses query exploration as the basis for search in video archives.

In this technical demonstration we showcase the current version of the MediaMill system, a search engine that facilitates access to news video archives at a semantic level. The core of the system is a thesaurus of 500 automatically detected semantic concepts. To handle such a large thesaurus in retrieval, an engine is developed which automatically selects a set of relevant concepts based on the textual query and userspecified example images. The result set can be browsed easily to obtain the final result for the query.

In this technical demonstration we show the current version of the MediaMill system, a search engine that facilitates access to news video archives at a semantic level. The core of the system is a lexicon of 436 automatically detected semantic concepts. To handle such a large lexicon in retrieval, an engine is developed which automatically selects a set of relevant concepts based on the textual query and example images. The result set can be browsed easily to obtain the final result for the query.

In this paper we present our Mediamill video search engine. The basis for the engine is a semantic indexing process which derives a lexicon of 101 concepts. To support the user in navigating the collection, the system defines a visual similarity space, a semantic similarity space, a semantic thread space, and browsers to explore them. It extends upon [1] with improved browsing tools. The search system is evaluated within the TRECVID benchmark [2]. We obtain a top-3 result for 19 out of 24 search topics. In addition, we obtain the highest mean average precision of all search participants.

In this technical demonstration we showcase the MediaMill system. A search engine that facilitates access to news video archives at a semantic level. The core of the system is an unprecedented lexicon of 100 automatically detected semantic concepts. Based on this lexicon we demonstrate how users can obtain highly relevant retrieval results using query-by-concept. In addition, we show how the lexicon of concepts can be exploited for novel applications using advanced semantic visualizations. Several aspects of the MediaMill system are evaluated as part of our TRECVID 2005 efforts.

Video is about to conquer the Internet. Real-time delivery of video content is technically possible to any desktop and mobile device, even with modest connections. The main problem hampering massive (re)usage of video content today is the lack of effective content based tools that provide semantic access. In this contribution we discuss systems for both video analysis and video retrieval that facilitate semantic access to video sources. Both systems were evaluated in the 2004 TRECVID benchmark as top performers in their task.

Goalgle is a prototype search engine for soccer video. Browsing and retrieval functionality is provided by means of a web based interface. This interface allows users to jump to video segments from a collection of prerecorded and analyzed soccer matches based on queries on specific players, events, matches, and/or text. In this contribution we discuss the system architecture and functionality of the Goalgle soccer video search engine.