Sign Finding and Reading SFAR on GPU Accelerated Mobile Devices

描述（由申请人提供）：无法访问印刷标志上的信息直接影响了美国120多万盲人的行动独立性。以前提出的许多解决这一问题的技术方案要么需要对环境进行物理修改（说话标志或放置编码标记），要么需要用户随身携带专用计算设备，这可能会使人感到耻辱。最近推行的一项战略是利用智能电话的计算能力和计算机视觉技术，使盲人能够使用市场上可买到的、非侮辱性的智能电话远距离阅读标志。然而，尽管存在复杂的算法来从杂乱的视频输入中识别和提取标志文本（例如，如通过诸如Google地图的地图服务自动定位并仅模糊街景地图中的牌照文本所证明的那样），但当前用于阅读标志的移动的解决方案 远距离文本性能相对较差。这种糟糕的性能很大程度上是因为直到最近，智能手机处理器还无法以实时速率执行最先进的计算机视觉文本提取和识别算法，这迫使以前的移动的标志阅读器利用较旧的、简单的、效率较低的算法。下一代智能手机运行在完全不同的混合处理器架构上（例如2013年发布的Tegra 4和Snapdragon 800），具有专用的嵌入式图形处理单元（GPU）和多核CPU，这使得它们非常适合高性能，视觉繁重的计算。在这项研究中，我们建议开发一个智能手机为基础的系统，寻找和阅读标志的距离，显着优于以前这样的读者通过实现国家的最先进的文本提取算法，现代智能手机混合GPU/CPU处理器架构。在第一阶段，将开发拟议的系统，并在盲人用户中进行测试。在第二阶段，来自用户测试的反馈将被纳入系统设计，性能将得到改善，以允许在极具挑战性的环境（如低光）下运行。

DESCRIPTION (provided by applicant): The inability to access information on printed signs directly impacts the mobility independence of the over 1.2 million blind persons in the U.S. Many previously proposed technological solutions to this problem either required physical modifications to the environment (talking signs or the placement of coded markers) or required the user to carry around specialized computational equipment, which can be stigmatizing. A recently pursued strategy is to utilize the computational capabilities of smart phones and techniques from computer vision to allow blind persons to read signs at a distance using commercially available, non-stigmatizing, smart- phones. However, despite the fact that sophisticated algorithms exist to recognize and extract sign text from cluttered video input (as evidenced, for example, by mapping services such as Google Maps automatically locating and blurring out only license plate text in street-view maps) current mobile solutions for reading sign text at a distance perform relatively poorly. This poor performance is largely because until recently, smart-phone processors have simply not been able to execute state-of-the-art computer vision text extraction and recognition algorithms at real-time rates, which forced previous mobile sign readers to utilize older, simplistic, less effective algorithms. Next-generation smart-phones run on fundamentally different, hybrid processor architectures (such as the Tegra 4, Snapdragon 800, both released in 2013) with dedicated embedded graphical processing units (GPUs) and multi-core CPUs, which make them ideal for high-performance, vision-heavy computation. In this study, we propose to develop a smart-phone-based system for finding and reading signs at a distance which significantly outperforms previous such readers by implementing state-of-the-art text extraction algorithms on modern smart-phone hybrid GPU/CPU processor architectures. In Phase I, the proposed system will be developed and tested with blind users. In Phase II, feedback from user testing will be integrated into system design and the performance will be improved to permit operation in extremely challenging (such as low light) environments.