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Sensor fusion for ecologically valid obstacle identification: Building a comprehensive assistive technology platform for the visually impaired

机译:传感器融合技术可有效地识别生态障碍:为视障者建立综合的辅助技术平台

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Sensor fusion represents a robust approach to ecologically valid obstacle identification in building a comprehensive electronic travel aid (ETA) for the blind and visually impaired. A stereoscopic camera system and an infrared sensor with 16 independent elements is proposed to be combined with a multi-scale convolutional neural network for this fusion framework. While object detection and identification can be combined with depth information from a stereo camera system, our experiments demonstrate that depth information may be inconsistent given material surfaces of specific potential collision hazards. This inconsistency can be easily remedied by supplementation with a more reliable depth signal from an alternate sensing modality. The sensing redundancy in this multi-modal strategy, as deployed in this platform, may enhance the situational awareness of a visually impaired end user, permitting more efficient and safer obstacle negotiation.
机译:传感器融合代表了一种健壮的方法,可在为盲人和视障者构建全面的电子旅行辅助系统(ETA)时,对生态学上的障碍物进行有效识别。针对此融合框架,建议将立体摄像系统和具有16个独立元素的红外传感器与多尺度卷积神经网络结合。虽然可以将物体检测和识别与来自立体摄像机系统的深度信息结合起来,但我们的实验表明,给定具有特定潜在碰撞危险的材料表面,深度信息可能会不一致。通过补充来自替代感应方式的更可靠的深度信号,可以轻松地纠正这种不一致。在此平台中部署的这种多模式策略中的感测冗余可以增强视力障碍最终用户的态势感知,从而实现更有效和更安全的障碍协商。

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