Feedback Driven Multi Stereo Vision System for Real-Time Event Analysis

Mohamed Benkedadra, M. Mancas, S. Mahmoudi
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Abstract

2D cameras are often used in interactive systems. Other systems like gaming consoles provide more powerful 3D cameras for short range depth sensing. Overall, these cameras are not reliable in large, complex environments. In this work, we propose a 3D stereo vision based pipeline for interactive systems, that is able to handle both ordinary and sensitive applications, through robust scene understanding. We explore the fusion of multiple 3D cameras to do full scene reconstruction, which allows for preforming a wide range of tasks, like event recognition, subject tracking, and notification. Using possible feedback approaches, the system can receive data from the subjects present in the environment, to learn to make better decisions, or to adapt to completely new environments. Throughout the paper, we introduce the pipeline and explain our preliminary experimentation and results. Finally, we draw the roadmap for the next steps that need to be taken, in order to get this pipeline into production.
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实时事件分析的反馈驱动多立体视觉系统
二维摄像机常用于交互式系统中。游戏机等其他系统提供更强大的3D摄像头,用于短距离深度感应。总的来说,这些摄像头在大型、复杂的环境中并不可靠。在这项工作中,我们提出了一个基于3D立体视觉的交互式系统管道,它能够处理普通和敏感的应用,通过强大的场景理解。我们探索多个3D相机的融合做全场景重建,这允许执行广泛的任务,如事件识别,主题跟踪和通知。使用可能的反馈方法,系统可以从环境中存在的主体接收数据,以学习做出更好的决策,或者适应全新的环境。在整个论文中,我们介绍了管道,并说明了我们的初步实验和结果。最后,我们为接下来需要采取的步骤绘制路线图,以便将该管道投入生产。
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