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Intelligent Image Processing and Signal Processing for wearable computing and AR (augmediated reality)

Intelligent Image Processing and Signal Processing for wearable computing and AR (augmediated reality)
用于可穿戴计算和 AR(增强现实)的智能图像处理和信号处理
批准号:
RGPIN-2014-06418
负责人:
Mann, Steve
金额:
$1.82万
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:
2014
资助国家:
加拿大
项目状态:
已结题
起止时间:
2014-01-01 至 2015-12-31

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中文摘要
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英文摘要
With ubiquitous mobile/portable imaging and computing now a reality, and wearable computing (e.g. Digital Eye Glass) just becoming a reality, we are entering an era in which our everyday lives are being or will soon be mediated by vision-based computers. Many of us already carry a camera and computing device (smartphone or cameraphone) most of the time. These devices will soon take the form of Digital Eye Glass to help many of us see better, and improve the quality of our lives. This technology will be especially welcome to the growing population of older individuals with failing eyesight. Moreover, as technologies become more personal, the Digital Eye Glass will help us remember names and faces (e.g. the wearable face recognizer), find our way (digital maps overlayed with Augmediated Reality), and provide us with improved safety (e.g. personal security), health (sensing, etc.) and well-being. From my long-standing personal experience (more than 35 years of inventing, designing, building, and experimenting with wearable computing and Digital Eye Glass since my childhood -- first as an amateur scientist in my youth, and later in my professional life), I have helped this industry evolve. Much of the industry is addressing immediate business interests, but there is a need for research on the foundational aspects of Intelligent Image Processing specifically related to personal imaging devices (small portable or wearable camera systems). In particular, a core issue that remains is getting cameras to "see" as well as the human eye does. Already the spatial resolution of cameras has increased from thousands of pixels to megapixels, but image quality (e.g. dynamic range) at each pixel has not kept pace. The first digital camera was invented (by Steven Sasson of Kodak) in 1975, and had 10,000 pixels (based on a Fairchild 100*100 pixel sensor), and 4 bits-per pixel per channel (1 channel, i.e. greyscale). Today, mobile and portable camera phones are up to 41 Megapixels (e.g. Nokia PureView 808), and some cameras are in the gigapixel range, i.e. spatial resolutions that are more than 100,000 times what they were in 1975. Thus many cameras can "see" the detail (e.g. "read" small print on a newspaper) thousands of times better now than then. But they still cannot match the human eye for dynamic range (i.e. being able to simultaneously sense in low-light and really bright light). Remarkably, the bit depth of modern cameras is typically only twice what the world's first digital camera was 38 years ago (8 bits compared to 4 bits). Recently I have addressed this problem by inventing and steadily improving something called HDR (High Dynamic Range) Imaging. Robertson et al. write:
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Intelligent Image Processing and Signal Processing for wearable computing and AR (augmediated reality)
  • 批准号:
    RGPIN-2014-06418
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.82万
  • 财政年份:
    2018
  • 负责人:
    Mann, Steve
  • 依托单位:
Intelligent Image Processing and Signal Processing for wearable computing and AR (augmediated reality)
  • 批准号:
    RGPIN-2014-06418
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.82万
  • 财政年份:
    2017
  • 负责人:
    Mann, Steve
  • 依托单位:
Intelligent Image Processing and Signal Processing for wearable computing and AR (augmediated reality)
  • 批准号:
    RGPIN-2014-06418
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.82万
  • 财政年份:
    2016
  • 负责人:
    Mann, Steve
  • 依托单位:
Intelligent Image Processing and Signal Processing for wearable computing and AR (augmediated reality)
  • 批准号:
    RGPIN-2014-06418
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.82万
  • 财政年份:
    2015
  • 负责人:
    Mann, Steve
  • 依托单位:
国内基金
海外基金
基于CE-3及IMAGE卫星地球等离子体层EUV探测数据的反演研究
Raw-Image微小物体高精度位姿测量法
  • 批准号:
    61105029
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    22.0万元
  • 批准年份:
    2011
  • 负责人:
    宋薇
  • 依托单位: