People with visual impairments face numerous challenges when interacting with
their environment. Our objective is to develop a device that facilitates
communication between individuals with visual impairments and their
surroundings. The device will convert visual information into auditory
feedback, enabling users to understand their environment in a way that suits
their sensory needs. Initially, an object detection model is selected from
existing machine learning models based on its accuracy and cost considerations,
including time and power consumption. The chosen model is then implemented on a
Raspberry Pi, which is connected to a specifically designed tactile device.
When the device is touched at a specific position, it provides an audio signal
that communicates the identification of the object present in the scene at that
corresponding position to the visually impaired individual. Conducted tests
have demonstrated the effectiveness of this device in scene understanding,
encompassing static or dynamic objects, as well as screen contents such as TVs,
computers, and mobile phones.

本文旨在开发一种设备，将视觉信息转换为听觉反馈，以协助视障者更好地了解他们的环境，该设备的选择基于准确性和成本方面的考虑，包括时间和功耗等因数，经测试，其在场景理解，包括静态或动态的对象，以及屏幕内容如电视、电脑和手机等方面具有显著的效果。