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The present work proposes the creation of a system that implements sensory substitution of vision through a wearable item with vibration motors positioned on the back of the user. In addition to the developed hardware, the proposal consists in the construction of a system that uses deep learning techniques to detect and classify objects in controlled environments. The hardware comprise of a simple HD camera, a pair of Arduinos, 9 cylindrical DC motors and a Raspberry Pi (responsible for the image processing and to translate the signal to the Arduinos). In the first trial of image classification and localization, the ResNet-50 model pre-trained with the ImageNet database was tried. Then we implemented a Single Shot Detector with a MobileNetV2 to perform real-time detection on the Raspberry Pi, sending the detected object class and location as defined patterns to the motors.

Vision Substitution with Object Detection and Vibrotactile Stimulus