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Vision algorithms for Emerging Applications

Vision algorithms for Emerging Applications
新兴应用的视觉算法
批准号:
RGPIN-2015-04974
负责人:
Shehata, Mohamed
金额:
$1.6万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
翻译
视频监控是加拿大乃至世界上发展最快的行业之一。据估计,2014年的收入将达到159亿美元,而2013年的收入为141亿美元。我们社会中的恐怖主义和高犯罪率需要更有效的监控系统。随着近年来图像传感器技术和飞行器的进步,空中监视已经成为一个非常活跃的领域,特别是2007年广域运动图像(WAMI)的引入。这些监视系统的核心是目标检测、跟踪和活动识别。***本研究计划研究广域运动图像(WAMI)中目标检测和跟踪的先进技术的设计和开发;具体而言,我们将探讨以下三个研究主题:三维空中重建,稳定和目标检测,以及目标跟踪。****在三维航空重建领域,我们将设计和开发新的算法,与传统的基于视差的算法不同,并使用密集匹配和全局优化技术。***在稳定和目标检测领域,我们将设计和开发一种新的鲁棒稳定技术,这样我们就可以将图像中不遵循稳定变换函数的异常值作为候选目标对象。我们将专注于解决和最小化视差和鬼影效果。***在目标跟踪领域,2014年的一项研究比较了WAMI中不同跟踪器的性能,得出的最佳性能精度为70%。这是由于高海拔和小物体尺寸在混乱的场景,特别是在高密度的运动区域与大量的物体。我们将设计新的算法,基于选定的滤波器响应在高维特征向量中表示对象。***提出的算法将使用分析和实验方法进行分析。该算法将在哥伦布大图像格式(CLIF)和VIVID数据集上进行测试,并通过使用飞行器来演示实时性能。该研究项目将有助于创建新的创新空中监视系统,该系统可用于广域Arial监视(WAAS)行业,WAAS是新兴技术之一,可提供城市规模的监视覆盖。***该研究项目还将为20-25名本科生和研究生提供培训,帮助他们在图像处理、计算机视觉、数字信号处理、优化、信息理论和计算复杂性分析等高级课题上建立强大的背景。学生将通过使用最先进的视觉设备和软件工具进行实验工作,并在有限资源的嵌入式板上实现算法,从而获得实践经验
英文摘要
Video surveillance represents one of the fastest growing industries in Canada and the world. It is estimated that the revenue will be $15.9 billion in 2014 compared $14.1 billion in 2013. Terrorism and high crime rates in our societies demand more efficient surveillance systems. With the recent advances in imagery sensor technology and aerial vehicles, aerial surveillance has become a very active area, especially with the introduction of Wide Area Motion Imagery (WAMI) in 2007. At the core of these surveillance systems are object detection, tracking, and activity recognition.***This research program investigates the design and development of advanced techniques for object detection and tracking in wide area motion imagery (WAMI); specifically, we will investigate the following three research themes: 3D aerial reconstruction, stabilization and object detection, and object tracking.****In the area of 3D aerial reconstruction, we will design and develop new algorithms that formulate the problem differently from the traditional disparity based algorithms and use dense matching and global optimization techniques.***In the area of stabilization and object detection, we will design and develop a new robust stabilization technique such that we can treat the outliers in the images that did not follow the transformation function from the stabilization as candidate target objects. We will focus on addressing and minimizing the parallax and ghost effects. ***In the area of object tracking, a recent study in 2014 compared the performance of different trackers in WAMI and concluded that the best performance accuracy achieved was 70%. This is due to high altitude and small object size in cluttered scenes, especially in high density motion areas with large number of objects. We will design new algorithms that represent the objects in higher dimensional feature vectors based on selected filter responses. ***The proposed algorithms will be analyzed using both analytical and experimental methods. The algorithms will be tested on Columbus Large Image Format (CLIF) and VIVID datasets, and also by using aerial vehicles to demonstrate real-time performance. ***This research program will help create new innovative aerial surveillance systems that can be used in the industry of Wide Area Arial Surveillance (WAAS), which is one of the emerging technologies that provide surveillance coverage in city-size coverage. ***This research program will also provide training to 20-25 undergraduate and graduate students in total helping them build strong backgrounds in advanced topics in image processing, computer vision, digital signal processing, optimization, information theory, and computational complexity analysis. The students will gain hands-on experience by performing experimental work using state-of-the-art vision equipment and software tools and implementing the algorithms on constrained resources embedded boards.**
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Advancing Object Detection and Tracking Frontiers in Intelligent Vision-Based Applications
  • 批准号:
    RGPIN-2022-03015
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2022
  • 负责人:
    Shehata, Mohamed
  • 依托单位:
Vision algorithms for Emerging Applications
  • 批准号:
    RGPIN-2015-04974
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2021
  • 负责人:
    Shehata, Mohamed
  • 依托单位:
Vision algorithms for Emerging Applications
  • 批准号:
    RGPIN-2015-04974
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2020
  • 负责人:
    Shehata, Mohamed
  • 依托单位:
Vision algorithms for Emerging Applications
  • 批准号:
    RGPIN-2015-04974
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2018
  • 负责人:
    Shehata, Mohamed
  • 依托单位:
国内基金
海外基金
固定参数可解算法在平面图问题的应用以及和整数线性规划的关系
  • 批准号:
    60973026
  • 项目类别:
    面上项目
  • 资助金额:
    32.0万元
  • 批准年份:
    2009
  • 负责人:
    鲁道夫
  • 依托单位:
Computational Methods for Analyzing Toponome Data