Ork de Rooij

MediaMill: exploring news video archives based on learned semantics

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.

Balancing thread based navigation for targeted video search

Various query methods for video search exist. Because of the semantic gap each method has its limitations. We argue that for effective retrieval query methods need to be combined at retrieval time. However, switching query methods often involves a change in query and browsing interface, which puts a heavy burden on the user. In this paper, we propose a novel method for fast and effective search trough large video collections by embedding multiple query methods into a single browsing environment. To that end we introduced the notion of query threads, which contain a shot-based ranking of the video collection according to some feature-based similarity measure. On top of these threads we define several thread-based visualizations, ranging from fast targeted search to very broad exploratory search, with the Fork-Browser as the balance between fast search and video space exploration. We compare the effectiveness and efficiency of the ForkBrowser with the CrossBrowser on the TRECVID 2007 interactive search task. Results show that different query methods are needed for different types of search topics, and that the ForkBrowser requires significantly less user interactions to achieve the same result as the CrossBrowser. In addition, both browsers rank among the best interactive retrieval systems currently available.

MediaMill: semantic video search using the RotorBrowser

In this technical demonstration we showcase the current version of the MediaMill system[1], 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.

Semantic document selection: historical research on collections that span multiple centuries

The availability of digitized collections of historical data, such as newspapers, increases every day. With that, so does the wish for historians to explore these collections. Methods that are traditionally used to examine a collection do not scale up to todays collection sizes. We propose a method that combines text mining with exploratory search to provide historians with a means of interactively selecting and inspecting relevant documents from very large collections. We assess our proposal with a case study on a prototype system.

Mediamill: advanced browsing in news video archives

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.

MediaMill: fast and effective video search using the forkbrowser

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.

Efficient targeted search using a focus and context video browser

Currently there are several interactive content-based video retrieval techniques and systems available. However, retrieval performance depends heavily on the means of interaction. We argue that effective CBVR requires efficient, specialized user interfaces. In this article we propose guidelines for such an interface, and we propose an effective CBVR engine: the ForkBrowser, which builds upon the principle of focus and context. This browser is evaluated using a combination of user simulation and real user evaluation. Results indicate that the ideas have merit, and that the browser performs very well when compared to the state-of-the-art in video retrieval.

The mediamill large.lexicon concept suggestion engine

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.

Instant Bag-of-Words served on a laptop

This demo showcases our realtime implementation of concept classification using the Bag-of-Words method embedded within MediaTable, our interactive categorization tool for large multimedia collections. MediaTable allows the users to open images from disk or download these directly from the internet. Each image is then processed using the Bag-of-Words method, which computes classification scores for 20 distinct concepts classes on the fly. These are then seamlessly displayed in the interface.

MediaTable: a tool for categorizing multimedia collections

In this technical demonstration, we present MediaTable, our interactive multimedia collection search and categorization tool. MediaTable allows users to search through, and categorize a multimedia collection with ease by employing several familiar interface components specifically adapted for multimedia collections. In our demonstration we expand on the visual interface, on how several types of search tasks can be completed with MediaTable.