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In the utilization of urban public facilities, it is found that the number of people under 18 years who exercise accounts for 29.5% of the total number of people surveyed, 32.8% between 18 and 65 years, and 37.7% over 65 years. The elderly have become the main population of public facilities, and the aging of cities is becoming more and more obvious. Strengthening the construction and development of urban public facilities has become the main work of current urban construction, and planning public facilities can effectively alleviate the pressure of urban public facilities. Through image recognition to promote urban sports public service, we improve the management efficiency of urban sports public service, facilitate residents' sports, and improve residents' satisfaction and happiness index. Through image recognition to manage portraits and objects, the safety of residents' sports and sports facilities is guaranteed, and the management efficiency is improved. The experimental results show that R-CNN, FAST R-CNN, and Faster R-CNN in urban public facilities can be intelligently recognized by image recognition technology for comparison. Faster R-CNN has good accuracy and low average time. Finally, the study analyzes the service cost of public facilities, compared with traditional public services, with the application of public services under image recognition, so as to guide different groups of people to make full use of public service facilities to improve their quality of life and realize the good behavior of the national movement.

Recognition and Optimization Analysis of Urban Public Sports Facilities Based on Intelligent Image Processing