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Automatic parsing of sports videos with grammars
Motivated by the analogies between languages and sports videos, we introduce a novel
approach for video parsing with grammars. It utilizes compiler techniques for integrating both semantic
annotation and syntactic analysis to generate a semantic index of events and a table of content for a given
sports video. The video sequence is first segmented and annotated by event detection with domain
knowledge. A grammar-based parser is then used to identify the structure of the video content.
Meanwhile, facilities for error handling are introduced which are particularly useful when the results of
automatic parsing need to be adjusted. As a case study, we have developed a system for video parsing in
the particular domain of TV diving programs. Experimental results indicate the proposed approach is
effectiv
Detecting complex events in user-generated video using concept classifiers
Automatic detection of complex events in user-generated
videos (UGV) is a challenging task due to its new characteristics differing from broadcast video. In this work, we firstly summarize the new characteristics of UGV, and then explore how to utilize concept classifiers to recognize complex events in UGV content. The method starts from manually selecting a variety of relevant concepts, followed byconstructing classifiers for these concepts. Finally, complex event detectors are learned by using the concatenated probabilistic scores of these concept classifiers as features. Further, we also compare three different fusion operations of probabilistic scores, namely Maximum, Average and Minimum fusion. Experimental results suggest that our method provides promising results. It also shows that Maximum fusion tends to give better performance for most complex events
“Transfer Talk” in Talk about Writing in Progress: Two Propositions about Transfer of Learning
This article tracks the emergence of the concept of “transfer talk”—a concept distinct from transfer of learning—and teases out the implications of transfer talk for theories of transfer of learning. The concept of transfer talk was developed through a systematic examination of 30 writing center transcripts and is defined as “the talk through which individuals make visible their prior learning (in this case, about writing) or try to access the prior learning of someone else.” In addition to including a taxonomy of transfer talk and analysis of which types occur most often in this set of conferences, this article advances two propositions about the nature of transfer of learning: (1) transfer of learning may have an important social, even collaborative, component and (2) although meta-awareness about writing has long been recognized as valuable for transfer of learning, more automatized knowledge may play an important role as well
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