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: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637471
• 关键词: Intelligent; Image; Processing; Signal; wearable

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:

随着无处不在的移动/便携式成像和计算现在成为现实，可穿戴计算(例如数字眼镜片)正在成为现实，我们正在进入一个我们的日常生活正在或即将由基于视觉的计算机来调节的时代。我们中的许多人大部分时间都已经携带了相机和计算设备(智能手机或照相手机)。这些设备将很快以数字眼镜片的形式出现，帮助我们中的许多人看得更好，并提高我们的生活质量。这项技术将特别受到越来越多视力不佳的老年人的欢迎。此外，随着技术变得更加个人化，数字眼镜会帮助我们记住名字和面孔(例如可穿戴的人脸识别器)，找到我们的路(数字地图覆盖了Augmedied Reality)，并为我们提供更好的安全性(例如个人安全性)和健康(传感等)。从我长期的个人经验(我从小发明、设计、建造和试验可穿戴计算和数字眼镜片--我年轻时作为一名业余科学家，后来在我的职业生涯中)，我帮助了这个行业的发展。该行业的许多人都在解决直接的商业利益，但有必要研究智能图像处理的基础方面，特别是与个人成像设备(小型便携式或可穿戴式摄像系统)相关的方面。尤其是，一个仍然存在的核心问题是让相机像人眼一样“看得见”。相机的空间分辨率已经从数千像素增加到百万像素，但每个像素的图像质量(例如动态范围)并没有跟上步伐。第一台数码相机(由柯达的Steven Sasson于1975年发明)，具有10,000像素(基于仙童100*100像素传感器)，每通道4位(1通道，即灰度)。今天，移动和便携式照相手机高达4100万像素(例如诺基亚PureView 808)，一些相机在千兆像素范围内，即空间分辨率是1975年的100,000倍以上。因此，许多相机现在可以比那时更好地“看到”细节(例如，“阅读”报纸上的小字体)。但它们在动态范围方面仍然比不上人眼(即能够同时在弱光和真正的强光下感知)。值得注意的是，现代相机的位深度通常只是38年前世界上第一台数码相机的两倍(8位比4位)。最近，我发明并稳步改进了一种名为HDR(高动态范围)的图像，从而解决了这个问题。Robertson等人。写道：