Abstract: A method and apparatus are provided for segmenting and summarizing a music video (507) in a multimedia stream (505) using content analysis. A music video (507) is segmented in a multimedia stream (505) by evaluating a plurality of content features that are related to the multimedia stream. The plurality of content features includes at least two of a face presence feature; a videotext presence feature; a color histogram feature; an audio feature, a camera cut feature; and an analysis of key words obtained from a transcript of the at least one music video. The plurality of content features are processed using a pattern recognition engine (1000), such as a Bayesian Belief Network, or one or more video segmentation rules (1115) to identify the music video (507) in the multimedia stream (505). A chorus is detected in at least one music video (507) using a transcript (T) of the music video (507) based upon a repetition of words in the transcript.

Abstract: Methods and systems for feature selection are described. In particular, methods and systems for feature selection for data classification, retrieval, and segmentation are described. Certain embodiments of the invention are directed to methods and systems for complement sort-merge tree (CSMT), fast-converging sort-merge tree (FSMT), and multi-level (ML) feature selection. Accurate and fast results may be obtained by the feature selection methods and systems described herein.

Abstract: A method, system and program product for evaluating annotations to content are described. Under aspects of the present invention, annotations made to content are received and evaluated for accuracy. Each annotation typically includes at least one element (e.g., terms) describing the content. The evaluation includes a syntactic level evaluation and at least one of a semantic level evaluation, a source level evaluation, a content level evaluation, or an annotator level evaluation. Based on the evaluations, feedback can be provided to an annotator making the annotations.

Abstract: A system, method, and program product for tracking content are described. Aspects of invention allow bodies of content, whether from a common channel or from different channels, to be compared for relatedness. Comparison of different bodies of content involves analyzing both the actual content, characteristics of the source(s) of the content, and optionally, elapsed time between their respective broadcasts/communications. To this extent, a content similarity value, a source characteristic value and an optional temporal value for the portions of content are determined, and then used to compute a relatedness value of the (bodies of) content.

Abstract: A method, system and program product developing an annotation lexicon are described. Under aspects of the present invention, annotation(s) to piece(s) of content are received and analyzed using one or more computational analyses. Based on the analyses, feedback will be generated to improve the annotation lexicon and/or the ontology thereof. Such improvement can lead to, among other things: the re-arrangement of interrelationships of terms in the annotation lexicon; the addition, modification or deletion of terms from the annotation lexicon; the re-arrangement or clustering of terms within the annotation lexicon; etc.

Abstract: A method and apparatus are provided for segmenting and summarizing a music video (507) in a multimedia stream (505) using content analysis. A music video (507) is segmented in a multimedia stream (505) by evaluating a plurality of content features that are related to the multimedia stream. The plurality of content features includes at least two of a face presence feature; a videotext presence feature; a color histogram feature; an audio feature, a camera cut feature; and an analysis of key words obtained from a transcript of the at least one music video. The plurality of content features are processed using a pattern recognition engine (1000), such as a Bayesian Belief Network, or one or more video segmentation rules (1115) to identify the music video (507) in the multimedia stream (505). A chorus is detected in at least one music video (507) using a transcript (T) of the music video (507) based upon a repetition of words in the transcript.

Abstract: Methods and systems for feature selection are described. In particular, methods and systems for feature selection for data classification, retrieval, and segmentation are described. Certain embodiments of the invention are directed to methods and systems for complement sort-merge tree (CSMT), fast-converging sort-merge tree (FSMT), and multi-level (ML) feature selection. Accurate and fast results may be obtained by the feature selection methods and systems described herein.

Abstract: A technique for semantic video compression is shown in block (120). Uncompressed video data (210), including a plurality of video data segments (S1, S2, . . . Sn), are organized into two or more buffer slots (220), such that each of the two or more buffer slots is filled with one or more of the received video data segments, thereby forming two or more buffered video portions corresponding to the two or more buffer slots. The buffered video data is then processed by a leaking rule, to extract one or more buffered video portions, while outputting one or more non-extracted buffered video portions, as compressed video data (230). The leaking rule data is stored in a histogram (240) and later used to organize and index data according to a users request.

Abstract: A method for selecting a subsequence of video frames (72-84) from a sequence of video frames (70) comprising defining a distance function between video frames (72-84) in the sequence of video frames (70). An optimization criterion is defined to express a feature of a plurality of subsequences of video frames (72-84) selected from the sequence of video frames (70). A method is disclosed for displaying key frames for browsing and streaming.