Early Representation and Analysis of Visual Spacetime

视觉时空的早期表示和分析

• 批准号: 249910-2012
• 负责人: Wildes, Richard
• 金额: $ 1.6万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=594362
• 关键词: Early; Representation; Analysis; Visual; Spacetime

The research that my collaborators and I carry out is in the general area of computer vision, the attempt to endow machines with a sense of sight. From a theoretical point of view this is an important endeavor as it bears on fundamental issues in complex information processing, and may yield results that bear on our understanding of visual information processing in natural systems (e.g., humans), as well. From a practical point of view, machines that can see have the potential to interact with humans in a much more natural and useful fashion than is currently the case. Our particular studies of visual information provide insights into the fundamental properties of temporal sequences of image (e.g., video) and extend our technological capabilities by indicating novel applications. We use mathematical techniques to analyze images, develop processing algorithms based on our analyses and carry out empirical tests to evaluate their performance. This allows us to ask basic questions about temporal sequences of images, a pervasive source of information about our surround world. Questions of interest include: How can complex streams of video be parsed into meaningful components (e.g., persistent structures and moving objects)? How can multiple views of a captured scene be used to reconstruct a three-dimensional model of the scene? This research contributes to Canada in three important ways. First, it advances the discipline of computer vision as we expose basic properties of image information and develop corresponding algorithms for incorporation into vision machines; this allows Canada to compete successfully in a critical area of science and technology. Second, it provides students with hands on experience and skills in vital areas of investigation, computer vision and, more generally, computer science. Students go on to make careers in science, technology, teaching and elsewhere, taking with them the enrichment of having been involved in research. Third, it paves the way for novel ways to practically exploit image data. Applications of interest include video processing for everyday concerns ranging from the internet to personal handheld devices, video enhancement so that content is more readily interpretable and intelligent processing modules for robots.

我和我的合作者进行的研究是在计算机视觉的一般领域，试图赋予机器视觉。从理论的角度来看，这是一项重要的努力，因为它涉及复杂信息处理的基本问题，并且可能产生影响我们对自然系统（例如人类）中视觉信息处理的理解的结果。从实用的角度来看，能看东西的机器有潜力以一种比目前更自然、更有用的方式与人类互动。我们对视觉信息的特殊研究提供了对图像（例如视频）时间序列的基本属性的见解，并通过指示新的应用扩展了我们的技术能力。我们使用数学技术来分析图像，根据我们的分析开发处理算法，并进行实证测试来评估其性能。这使我们能够提出关于图像时间序列的基本问题，这是关于我们周围世界的普遍信息来源。感兴趣的问题包括：如何将复杂的视频流解析为有意义的组件（例如，持久结构和移动对象）？如何使用捕获场景的多个视图来重建场景的三维模型？这项研究在三个重要方面为加拿大做出了贡献。首先，它促进了计算机视觉学科的发展，因为我们揭示了图像信息的基本属性，并开发了相应的算法用于视觉机器；这使得加拿大能够在一个关键的科学和技术领域成功竞争。其次，它为学生提供了在调查、计算机视觉以及更广泛的计算机科学等重要领域的实践经验和技能。学生们将继续从事科学、技术、教学和其他领域的职业，并从参与研究中获得丰富的经验。第三，为实际利用图像数据的新方法铺平了道路。感兴趣的应用包括日常关注的视频处理，从互联网到个人手持设备，视频增强，使内容更容易解释和机器人的智能处理模块。