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Spatiotemporal Models for Analyzing and Understanding Video

Spatiotemporal Models for Analyzing and Understanding Video
用于分析和理解视频的时空模型
批准号:
435926-2013
负责人:
Derpanis, Konstantinos
金额:
$1.46万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
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英文摘要
**Video contains a wealth of information for understanding and manipulating the surrounding world; however, in its raw form as a set of pointwise intensities, video fails to make explicit pertinent information available for further processing. The proposed research program aims to explore methods to extract useful information from raw video streams for further analysis, starting at the earliest stages of processing. Over the next five years, the following three basic questions of inquiry will be examined. What makes a useful part decomposition of human actions for automatically recognizing them in a video stream? How can appearance and dynamic information in video be used simultaneously to recover the three dimensional geometric layout of an imaged scene? How can the observed collective behaviours of a densely packed ensemble of individuals aid in tracking each individual? These three basic questions will be addressed via a tight coupling of mathematical models of temporal imagery, the development of novel algorithms (e.g., image processing) and systematic empirical evaluation with both controlled synthetic and real data. The proposed research is innovative in three primary ways. First, the research program offers broad theoretical insights into our fundamental understanding of information available in raw video. Second, these insights provide the firm foundation for the development of algorithms addressing a variety of practical vision-based applications. For example, action recognition can be used for video indexing and browsing, 3D structure recovery is a key part of developing autonomous robots, and tracking in large densely populated areas can aid in security, safety and public space design. Third, it gives students the opportunity to develop their technical and analytical skills in the area of computer vision and more generally the emerging field of data science. This training prepares students for careers in academic or industrial research and development.**********************
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Deep Video Analysis
  • 批准号:
    RGPIN-2019-04623
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2022
  • 负责人:
    Derpanis, Konstantinos
  • 依托单位:
Deep Video Analysis
  • 批准号:
    RGPIN-2019-04623
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2021
  • 负责人:
    Derpanis, Konstantinos
  • 依托单位:
Deep Video Analysis
  • 批准号:
    RGPIN-2019-04623
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2020
  • 负责人:
    Derpanis, Konstantinos
  • 依托单位:
Deep Video Analysis
  • 批准号:
    RGPIN-2019-04623
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2019
  • 负责人:
    Derpanis, Konstantinos
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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