However, common screens are often evaluated using subjective visual detection of a priori prescribed discrete movement features (e.g., spine angle at maximum squat depth) and may not account for whole-body movement coordination, or associations between different discrete features.Objective ![]() Movement screens are increasingly used in sport and rehabilitation to evaluate movement competency. The expected possible result is a system that integrates the four stages mentioned above through an intuitive and accessible low-cost Python API, mainly aimed at visually impaired people. Finally, the fourth stage is to interpret the result and play it through a speaker. The third stage seeks to segment the object of study by artificial vision techniques to identify the result of the dice after being thrown. The second stage corresponds to the captured image processing it is necessary to establish a standard image size and resize and equalize the digitized image. The first one is capturing images through a device with a digital camera connected to the web via IP address. ![]() The software is structured in four stages. ![]() This work presents the development of a Python API to identify the result of two six-sided dice used in the game called “Craps” as a no-controlled environment to help visually impaired people. Pattern recognition is a prominent area of research in computer vision, where different methods have been proposed in the last 50 years.
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June 2023
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