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Outline

Goal : Promote progress in content-based retrieval from digital video ... Collected from Internet Archive and Open Video websites, documentaries from the ...

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Outline

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    Slide 2:Outline Summary of TREC Video Track Automatic Retrieval Task Our Method and System Architecture Video Retrieval Demo

    Slide 3:2002 TREC Video Retrieval Task Goal : Promote progress in content-based retrieval from digital video via open, metrics-based evaluation. Query 25 queries Text, Image(Optional), Video(Optional) Search Collection Total Length: 40.16 hours MPEG-1 format Collected from Internet Archive and Open Video websites, documentaries from the ‘50s 14,000 shots 292,000 I-frames (images)

    Slide 4:Sample Query XML Representation

    Slide 5:Sample Query Text : Find pictures of George Washington

    Slide 6:System Architecture (Last Year) Simply weighted linear combination of video, audio and text retrieval score

    Slide 7:System Architecture (This Year) New step: Classification through Pseudo Relevance Feedback (PRF) Combine with movie information agent (abstract, title)

    Slide 8:What is Pseudo Relevance Feedback Relevance Feedback (Human intervention)

    Slide 9:Classification from Modified PRF Automatic retrieval technique Modification: use negative data as feedback Step-by-step Run base retrieval algorithm on image collection Nearest neighbor(NN) on color and texture Build classifier Negative examples: least relevant images in the collection Positive examples: image queries Classify all data in the collection

    Slide 10:Combination of Agents Multiple Agents Text Retrieval Agent Movie Information Retrieval Agent Base Image Retrieval Agent Nearest Neighbor on Color Nearest Neighbor on Texture One-class SVM ( not used in TREC ) Classification PRF Agent Combination of multiple agents Convert scores to posterior probability Linear combination

    Slide 11:Demo Queries window Agents (Query Menu)

    Slide 12:Demo : Query Expansion through Text Expand the query with google image search engine Text Queries ? images Didn’t work as expected (Not used in TREC) Future work

    Slide 13:Demo : Results Menu Show retrieval results (pre-computed) Answer key window Results window Sort by different agents Rank vs Score Display results

    Slide 14:Demo 5: Result statistics Show result statistics window Show comparative performance Ranking in all the participants Rank 3rd in 27 participating systems

    Slide 15:Discussion & Future Work Discussion The result is sensitive to the queries with small number of answers Images only is not enough to represent the semantics Future Work Incorporate more agents Utilize the relationship between multiple agent information Better combination scheme

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