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首页> 外文会议>IEEE International Conference on Real-time Computing and Robotics >Perception Framework through Real-Time Semantic Segmentation and Scene Recognition on a Wearable System for the Visually Impaired
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Perception Framework through Real-Time Semantic Segmentation and Scene Recognition on a Wearable System for the Visually Impaired

机译：通过实时语义分割和现场识别在视觉损害的可穿戴系统上的实时语义分割和场景识别的感知框架

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摘要

As the scene information, including objectness and scene type, are important for people with visual impairment, in this work we present a multi-task efficient perception system for the scene parsing and recognition tasks. Building on the compact ResNet backbone, our designed network architecture has two paths with shared parameters. In the structure, the semantic segmentation path integrates fast attention, with the aim of harvesting long-range contextual information in an efficient manner. Simultaneously, the scene recognition path attains the scene type inference by passing the semantic features into semantic-driven attention networks and combining the semantic extracted representations with the RGB extracted representations through a gated attention module. In the experiments, we have verified the systems' accuracy and efficiency on both public datasets and real-world scenes. This system runs on a wearable belt with an Intel RealSense LiDAR camera and an Nvidia Jetson AGX Xavier processor, which can accompany visually impaired people and provide assistive scene information in their navigation tasks.
机译：作为场景信息，包括对象和场景类型，对于具有视觉损伤的人来说很重要，在这项工作中，我们为场景解析和识别任务提供了一个多任务高效的感知系统。在Compact Reset骨干上构建，我们设计的网络架构有两个具有共享参数的路径。在结构中，语义分割路径集成了快速关注，目的是以有效的方式收集远程上下文信息。同时，场景识别路径通过将语义特征传递到语义驱动的注意网络并将语义提取的表示与RGB提取的表示通过所喷射的注意模块组合来实现场景类型推断。在实验中，我们已经验证了对公共数据集和现实世界场景的系统准确性和效率。该系统在可穿戴带上的可穿戴皮带上运行，带有英特尔Realsense Lidar Camera和NVIDIA Jetson Agx Xavier处理器，可以伴随着视力受损人员，并在其导航任务中提供辅助场景信息。

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