ITR: Distributed Smart Cameras: Algorithms, Architectures, and Synthesis

ITR：分布式智能相机：算法、架构和综合

• 批准号: 0325119
• 负责人: Shuvra Shikhar Bhattacharyya
• 金额: $ 168万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0325119&HistoricalAwards=false
• 关键词: ITR; Distributed; Smart; Cameras; Algorithms

We propose to develop novel techniques and methodologies for distributed smart camera networks through an integrated exploration of distributed algorithms, embedded architectures, and software synthesis techniques. We will develop new architectures and tools that are designed to tackle modern video processing algorithms. The algorithms will leverage distributed architectures for efficient implementations. We will investigate a series of complex smart camera algorithms drawn from surveillance and biometrics applications. Specifically, we will be investigating efficient implementations of algorithms for self-calibration of distributed cameras, view-synthesis using image-based visual hulls, and human identification using face and gait. Networks of distributed cameras are an emerging enabling technology for a broad range of important information technology applications, including surveillance, biometrics, and smart conference rooms. By having acces to scenes from multiple directions, such networks have the potential for complete views than single-camera systems. This contributes to increased robustness and generality of algorithms. However, this distributed nature, coupled with the inherent challenges associated with real-time video processing, greatly complicates the devlopment of effective algorithms, architectures and software.An integrated research program inclduing video, design tools, and embedded system architecture is required to understand how new generation ofsmart camera hardware can be best utilized.

我们建议开发新的分布式智能摄像机网络的技术和方法，通过分布式算法，嵌入式架构和软件合成技术的综合探索。我们将开发新的架构和工具，旨在解决现代视频处理算法。这些算法将利用分布式架构来实现高效的实现。我们将研究一系列复杂的智能相机算法，这些算法来自于监控和生物识别应用。具体来说，我们将研究分布式摄像机自校准算法的有效实现，使用基于图像的视觉外壳进行视图合成，以及使用面部和步态进行人体识别。分布式摄像机网络是一种新兴的支持技术，适用于广泛的重要信息技术应用，包括监控、生物识别和智能会议室。通过从多个方向访问场景，这样的网络比单摄像机系统具有完整视图的潜力。这有助于提高算法的鲁棒性和通用性。然而，这种分布式的性质，再加上与实时视频处理相关的固有挑战，极大地复杂化了有效的算法，架构和software.A集成的研究计划inclduing视频，设计工具，和嵌入式系统架构的发展需要了解如何新一代的智能摄像头硬件可以最好地利用。