This technology offers the possibility to classify videos according to the respective genre (e.g. "Cartoon" and "Non-Cartoon"). This can be used both for private home use and for the automatic classification of audiovisual data for the Internet and search engines.
This technology is suitable for consumer electronics, especially for recording a video signal, and can be used by large video archives or by any other industry dealing with the problem described.
This technology for video-genre classification developed at TU Berlin provides applications for personal video recorders and for an automatic classification of audio-visual data for the internet and for search engines.
A main challenge in the field of multimedia content analysis is the transformation of human interpretations of audio-visual data to correlating machine processable representations.
This invention analyses such contents with the help of high-level audio-visual descriptors and of classification methods. To give an example: If you wish to distinguish between the genres ‘cartoon’ and ‘non-cartoon’, the performance of several combinations of the newly developed descriptors and classification methods is analyzed.
A classification accuracy (CA) of 95.6 % is achieved by using two hidden Markov models (HMM). For the distinction between the features ‘commercial’ and ‘non-commercial’ a CA of 98.4 % can be achieved by using two HMM. A decision tree results in a CA of 95.5 % for music videos and a CA of 91.9 % for news. When distinguishing between ‘sport’ and ‘non-sport’, Bayes’ Theorem achieves a CA of 95.2 %.
Ina Krüger
Technology Transfer Manager
+49 (0)30 314-75916
ina.krueger@tu-berlin.de
Technology validated in lab
approved: US
Technische Universität Berlin
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