RI: Small: Collaborative Research: Contour-Assisted Visual Inference: Systems, Algorithms, and Applications

遮挡轮廓（OC）在许多计算机视觉任务中发挥着重要作用。与常规照片不同，OC图像消除了照明，纹理和外观的影响，同时保留了重要的深度边缘和轮廓。该项目开发了一个全面的框架，用于在视觉推理任务中获取、处理和利用OCs。在传感器方面，研究小组开发了一种新的遮挡轮廓相机或OC-Cam。新的OC-Cam通过耦合一组可控红外（IR） led和一对可见-红外相机扩展了多闪光灯相机。在算法和应用方面，研究团队系统地开发了oc辅助视觉推理算法。在识别方面，将获取的oc作为特征滤波器来提高类别级目标的识别。对于跟踪，pi应用OCs通过过滤掉背景和纹理边缘来增强目标表示。此外，研究小组调查了以前未被充分探索的oc辅助图像摘要和隐私保护问题。这个项目可以在研究和教育方面对计算机视觉、人工智能、刑事司法和机器人等广泛领域产生深远影响。由于OCs在人类视觉中的重要性，研究结果可以为视觉心理学的研究提供一个试验台。此外，OC-Cam预计将作为构建下一代监视系统的概念灵感。最后，将捕获的OC数据集和相关工具提供给其他研究人员，为验证新的基于OC的计算机视觉算法提供一个平台。

Occlusion contour (OC) is well known to play important roles in many computer vision tasks. Unlike regular photographs, an OC image removes the effects of illumination, texture, and appearance while preserving important depth edges and silhouette. This project develops a comprehensive framework for acquiring, processing, and utilizing OCs in visual inference tasks. On the sensor front, the research team develops a new Occlusion Contour Camera or OC-Cam. The new OC-Cam extends the multi-flash camera by coupling an array of controllable infrared (IR) LEDs and a visible-IR camera pair. On the algorithm and application fronts, the research team systematically develops OC-assisted visual inference algorithms. For recognition, the acquired OCs are used as a feature filter to improve category-level object recognition. For tracking, the PIs apply OCs to enhance target representation by filtering out the background and texture edges. Furthermore, the research team investigates the previously under-explored problems of OC-assisted image summarization and privacy protection.This project can cast deep impact on broad areas of computer vision, artificial intelligence, criminal justices, and robotics, both in research and education. Due to the importance of OCs in human vision, the results can produce a testbed for the study of visual psychology. Furthermore, the OC-Cam is expected to serve as conceptual inspiration for constructing the next-generation surveillance systems. Finally, the captured OC datasets and relevant tools are made available to other researchers, to provide a platform for validating new OC-based computer vision algorithms.