• Title/Summary/Keyword: Multiple Similar Sub-Trajectory Retrieval

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Similar Sub-Trajectory Retrieval based on k-warping Algorithm for Moving Objects in Video Databases (비디오 데이타베이스에서 이동 객체를 위한 k-워핑 알고리즘 기반 유사 부분궤적 검색)

  • 심춘보;장재우
    • Journal of KIISE:Databases
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    • v.30 no.1
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    • pp.14-26
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    • 2003
  • Moving objects' trajectories play an important role in indexing video data on their content and semantics for content-based video retrieval. In this paper, we propose new similar sub-trajectory retrieval schemes based on k-warping algorithm for efficient retrieval on moving objects' trajectories in video data. The proposed schemes are fixed-replication similar sub-trajectory retrieval(FRSR) and variable-replication similar sub-trajectory retrieval(VRSR). The former can replicate motions with a fixed number for all motions being composed of the trajectory. The latter can replicate motions with a variable number. Our schemes support multiple properties including direction, distance, and time interval as well as a single property of direction, which is mainly used for modeling moving objects' trajectories. Finally, we show from our experiment that our schemes outperform Li's scheme(no-warping) and Shan's scheme(infinite-warping) in terns of precision and recall measures.

ECoMOT : An Efficient Content-based Multimedia Information Retrieval System Using Moving Objects' Trajectories in Video Data (ECoMOT : 비디오 데이터내의 이동체의 제적을 이용한 효율적인 내용 기반 멀티미디어 정보검색 시스템)

  • Shim Choon-Bo;Chang Jae-Woo;Shin Yong-Won;Park Byung-Rae
    • The KIPS Transactions:PartB
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    • v.12B no.1 s.97
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    • pp.47-56
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    • 2005
  • A moving object has a various features that its spatial location, shape, and size are changed as time goes. In addition, the moving object has both temporal feature and spatial feature. It is one of the highly interested feature information in video data. In this paper, we propose an efficient content-based multimedia information retrieval system, so tailed ECoMOT which enables user to retrieve video data by using a trajectory information of moving objects in video data. The ECoMOT includes several novel techniques to achieve content-based retrieval using moving objects' trajectories : (1) Muitiple trajectory modeling technique to model the multiple trajectories composed of several moving objects; (2) Multiple similar trajectory retrieval technique to retrieve more similar trajectories by measuring similarity between a given two trajectories composed of several moving objects; (3) Superimposed signature-based trajectory indexing technique to effectively search corresponding trajectories from a large trajectory databases; (4) convenient trajectory extraction, query generation, and retrieval interface based on graphic user interface