This study aims to explore the application of computer vision technology in smart home environments and its influence on space design optimization. Through the comprehensive application of image recognition and processing technology, the behavior patterns of family members, the placement status of household items, and the real-time changes in the indoor environment in smart home systems are deeply analyzed. The experimental results show that computer vision technology can effectively improve smart home systems’ perception and analysis ability, providing data support for automatically adjusting indoor environments and providing personalized service. At the same time, this study also focuses on the optimization strategy of space design based on computer vision technology and puts forward a series of humanized design schemes through reasonable arrangement of cameras and sensors, real-time analysis of user behavior data and environmental parameters, aiming at improving living comfort and achieving efficient use of energy. This study reveals the internal relationship between computer vision technology and space design, which complement each other and jointly promote the intelligent and humanized development of smart homes.