In this paper, we propose a new video genre detection using semantic classification with multi-modal features. MPEG-7 audio-visual descriptors are used as multi-modal features. Fr...
In this paper, we propose an audio-visual approach to video genre categorization. Audio information is extracted at block-level, which has the advantage of capturing local temporal...
Bogdan Ionescu, Klaus Seyerlehner, Christoph Rasch...
Thispaper presents a set of computationalfeatures originatingfrom our study of editing effects, motion, and color used in videos,for the task of automatic video categorization. Th...
We present a novel genre-independent SVM framework for detecting scene changes in broadcast video. Our framework works on content from a diverse range of genres by allowing sets o...
Naveen Goela, Kevin W. Wilson, Feng Niu, Ajay Diva...
This paper presents the status of a project targeting the development of content-based video indexing tools, to assist a human in the generation of descriptive video for the hard ...