The integration of computer vision techniques and technologies has become increasingly prevalent in designing natural and intuitive interactions, particularly in extended reality environments. This study aims to explore current trends, challenges, and practices in utilizing computer vision for interactive media design. A systematic literature review was conducted following PRISMA guidelines, based on a PICO-structured eligibility framework. From 94 reviewed studies, 11 computer vision techniques were identified in the design of interactions across virtual, augmented, and mixed realities. Emerging trends and technological dependencies were examined by considering design contexts, user interface utilization, hardware preferences, software libraries, and machine learning models. While many existing studies combine multiple computer vision techniques, this study provides a detailed categorization that clarifies their practical applications in interaction design. The study offers both a reference framework for future research and a practical guide for designers, researchers, and novice practitioners seeking to integrate computer vision into interactive media.