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• W1480606888 abstract "This thesis is concerned with the automatic generation of natural language descriptionsthat can be used for video indexing, retrieval and summarization applications.It is a step ahead of keyword based tagging as it captures relations between keywordsassociated with videos, thus clarifying the context between them. Initially,we prepare hand annotations consisting of descriptions for video segments craftedfrom a TREC Video dataset. Analysis of this data presents insights into humansinterests on video contents. For machine generated descriptions, conventional imageprocessing techniques are applied to extract high level features (HLFs) fromindividual video frames. Natural language description is then produced based onthese HLFs. Although feature extraction processes are erroneous at various levels,approaches are explored to put them together for producing coherent descriptions.For scalability purpose, application of framework to several different video genresis also discussed. For complete video sequences, a scheme to generate coherent andcompact descriptions for video streams is presented which makes use of spatial andtemporal relations between HLFs and individual frames respectively. Calculatingoverlap between machine generated and human annotated descriptions concludesthat machine generated descriptions capture context information and are in accordancewith human’s watching capabilities. Further, a task based evaluation showsimprovement in video identification task as compared to keywords alone. Finally,application of generated natural language descriptions, for video scene classificationis discussed." @default.
• W1480606888 created "2016-06-24" @default.
• W1480606888 creator A5007976764 @default.
• W1480606888 date "2012-09-14" @default.
• W1480606888 modified "2023-09-27" @default.
• W1480606888 title "Natural language descriptions for video streams" @default.
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