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Stereo Vision Based Sensory Substitution for the Visually Impaired

机译:基于立体视觉的视障者的感官替代

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摘要

The development of computer vision based systems dedicated to help visually impaired people to perceive the environment, to orientate and navigate has been the main research subject of many works in the recent years. A significant ensemble of resources has been employed to support the development of sensory substitution devices (SSDs) and electronic travel aids for the rehabilitation of the visually impaired. The Sound of Vision (SoV) project used a comprehensive approach to develop such an SSD, tackling all the challenging aspects that so far restrained the large scale adoption of such systems by the intended audience: Wearability, real-time operation, pervasiveness, usability, cost. This article is set to present the artificial vision based component of the SoV SSD that performs the scene reconstruction and segmentation in outdoor environments. In contrast with the indoor use case, where the system acquires depth input from a structured light camera, in outdoors SoV relies on stereo vision to detect the elements of interest and provide an audio and/or haptic representation of the environment to the user. Our stereo-based method is designed to work with wearable acquisition devices and still provide a real-time, reliable description of the scene in the context of unreliable depth input from the stereo correspondence and of the complex 6 DOF motion of the head-worn camera. We quantitatively evaluate our approach on a custom benchmarking dataset acquired with SoV cameras and provide the highlights of the usability evaluation with visually impaired users.
机译:近年来,基于计算机视觉的系统的开发致力于帮助视障人士感知环境,定向和导航,这已成为许多作品的主要研究主题。已使用大量资源来支持感官替代设备(SSD)和电子旅行辅助设备的开发,以帮助视障者康复。视觉之声(SoV)项目采用了一种综合方法来开发这样的SSD,解决了迄今为止限制了目标受众大规模采用此类系统的所有挑战性方面:可穿戴性,实时操作,普及性,可用性,成本。本文旨在介绍SoV SSD的基于人工视觉的组件,该组件在室外环境中执行场景重建和分割。与室内用例相反,在室内用例中,系统从结构化的摄像头获取深度输入,而在户外,SoV依靠立体视觉来检测感兴趣的元素,并向用户提供环境的音频和/或触觉表示。我们的基于立体声的方法旨在与可穿戴式采集设备配合使用,并且在立体声对应的不可靠的深度输入以及头戴式摄像机的复杂6自由度运动的情况下,仍可提供场景的实时,可靠描述。我们使用SoV摄像机获取的自定义基准数据集对方法进行定量评估,并为视障用户提供可用性评估的重点。

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