Abstract: An embodiment of the present invention relates to the combining of multiple semantic analyses of audio-visual data in order to resolve a higher fidelity description of the semantic content and more specifically to a method for applying semantic concept detection over multiple related audio-video sources, scoring the sources on the basis of presence or absence of specific semantics and aggregating the scores using combination functions to achieve a semantic super-resolution.

Abstract: A computer implemented method and computer program product for automatically building semantic associations within a database of unstructured information includes an algorithm for mapping data within the unstructured information and iteratively improving semantic labels for association with the data, until such point as associations pass a convergence test and then the semantic associations are made.

Abstract: Methods and apparatus for optimizing resource allocation among data analysis functions in a classification system are provided. Each of the data analysis functions is characterized as a set of operating points in accordance with at least one of resource requirements and analysis quality. An operating point for each of the data analysis functions is selected in accordance with one or more constraints. The analysis functions are applied at selected operating points to optimize resource allocation among the data analysis functions in the classification system.

Abstract: The present invention relates to the use of search fusion methods for querying multimedia databases and more specifically to a method and system for constructing a multi-modal query of a multimedia repository by forming multiple uni-modal searches and explicitly selecting fusion methods for combining their results. The present invention also relates to the integration of search methods for content-based retrieval, model-based retrieval, text-based retrieval, and metadata search, and the use of graphical user interfaces allowing the user to form queries fusing these search methods.

Abstract: Semantic indexing and retrieval of multimedia content requires that the content is sufficiently annotated. However, the great volumes of multimedia data and diversity of labels make annotation a difficult and costly process. Disclosed is an annotation framework in which supervised training with partially labeled data is facilitated using active learning. The system trains a classifier with a small set of labeled data and subsequently updates the classifier by selecting a subset of the available data-set according to optimization criteria. The process results in propagation of labels to unlabeled data and greatly facilitates the user in annotating large amounts of multimedia content.

Abstract: An apparatus and method for analyzing multimedia content to identify the presence of audio, visual and textual cues that together correspond to one or more high-level semantics are provided. The apparatus and method make use of one or more analysis models that are trained to analyze audio, visual and textual portions of multimedia content to generate scores associated with the audio, visual and textual portions with respect to various high-level semantic concepts. These scores are used to generate a vector of scores. The apparatus is trained with regard to relationships between audio, visual and textual scores to thereby take the vector of scores generated for the multimedia content and classify the multimedia content into one or more high-level semantic concepts. Based on the scores for the various audio, video and textual portions of the multimedia content, a level of certainty regarding the high-level semantic concepts may be generated.

Abstract: A method, system and computer program for adaptively processing a query search. An expanding operation is utilized to expand the query into sub-queries, wherein at least one of the sub-queries is expanded probabilistically. A retrieving operation retrieves the results of the sub-queries, and a merging operation is used to merge the sub-query results into a search result. An adapting operation is configured to modify the search such that the relevance of the search result is increased when the search is repeated.

Abstract: A method for performing content-based temporal segmentation of video sequences, the method comprises the steps of transmitting the video sequence to a processor; identifying within the video sequence a plurality of type-specific individual temporal segments using a plurality of type-specific detectors; analyzing and refining the plurality of type-specific individual temporal segments identified in the identifying the plurality of type-specific individual temporal segments step; and outputting a list of locations within the video sequence of the identified type-specific individual temporal segments.

Abstract: A method for performing content-based temporal segmentation of video sequences, the method comprises the steps of transmitting the video sequence to a processor; identifying within the video sequence a plurality of type-specific individual temporal segments using a plurality of type-specific detectors; analyzing and refining the plurality of type-specific individual temporal segments identified in the identifying the plurality of type-specific individual temporal segments step; and outputting a list of locations within the video sequence of the identified type-specific individual temporal segments.

Abstract: A method for performing content-based temporal segmentation of video sequences, the method comprises the steps of transmitting the video sequence to a processor; identifying within the video sequence a plurality of type-specific individual temporal segments using a plurality of type-specific detectors; analyzing and refining the plurality of type-specific individual temporal segments identified in the identifying the plurality of type-specific individual temporal segments step; and outputting a list of locations within the video sequence of the identified type-specific individual temporal segments.

Abstract: A method for performing content-based temporal segmentation of video sequences, the method comprises the steps of transmitting the video sequence to a processor, identifying within the video sequence a plurality of type-specific individual temporal segments using a plurality of type-specific detectors; analyzing and refining the plurality of type-specific individual temporal segments identified in the identifying the plurality of type-specific individual temporal segments step; and outputting a list of locations within the video sequence of the identified type-specific individual temporal segments.