This research explores the application of Motion Capture (MoCap) technology in 3D animation, discussing the potential of algorithms in understanding human motion and enhancing motion capture technology. Through a comprehensive review, the study identifies the strengths and limitations of motion capture systems, emphasizing the importance of maintaining a balance between accessibility and quality in the process. The research utilizes a literature review and comprehensive analysis of motion capture technology in the context of 3D animation as its methodology. Literature sources were acquired from online journal databases such as IEEE, Google Scholar, and ScienceDirect. The literature analysis involves four phases of approach, including data extraction and systematic evaluation of the content of each source. The study reveals several challenges, including the complexity of synchronizing motion data with 3D models, understanding algorithms for human motion, and improving motion capture technology. Additionally, the research highlights the potential of machine learning algorithms to enhance the accuracy and efficiency of motion capture data processing. The research findings emphasize the importance of maintaining a balance between accessibility and quality when selecting motion capture systems for 3D animation production. Furthermore, machine learning algorithms are detected to improve the accuracy and efficiency of motion capture data processing. Identified challenges include integrating motion capture into 3D animation production, considering costs, and resource requirements, and integration with animation software. The potential use of motion capture in film production, video games, and other applications provides insights into the significant impact of this technology on the visual experience for audiences. In summary, this study offers an extensive examination of the motion capture procedure, as well as its potential and obstacles within the domain of 3D animation.