The diploma thesis consists of a theoretical as well as a practical aspect of development of a device, which is based on computer vision methods, especially object detection, and is intended to help blind users by transforming the results of obstacle detection data into audio data, which is then played back to the users. The first step is to obtain a sequence of 3D point clouds from a stereo camera, as the camera allows the recording of depth. Next, the point cloud data is used as input data for object detection algorithms. It is imperative for the system to detect the objects of importance to the user, such as pedestrians, vehicles, curbs, stairs and other obstacles on the user's path. The results are transformed into an audio signal, which clearly and in real-time notifies the user about the distance of approaching objects via various sounds. The final result enhances the blind user's experience when walking in a city environment by playing warning sounds in real-time and thereby reducing the danger of accidents, such as colliding with and losing balance over obstacles. The system also gives more contextual information of the user's surroundings.
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