Exploring the Application of Computer Visual Arts in the Context of Digital Media

Abstract

This paper provides an in-depth discussion on the critical technologies of computer visual arts in digital media, mainly focusing on virtual character modeling and human body tracking technologies. The study merges the models into the same coordinate system by combining point cloud data from different angles and calculating the transformation matrix. Accurate 3D human body models were reconstructed using point cloud alignment and fusion techniques. A particle filtering method combined color, motion and shape information for effective tracking. The experimental results show that the success rate of hand tracking reaches 95.35% in the case of no background interference, while the success rate is 90.97% in the environment with background interference. In addition, the study shows that low resolution images (584×388) outperform high resolution (968×676) in terms of tracking accuracy and speed. The study confirms that the combination of advanced computer vision techniques can effectively construct and follow virtual character models and realize high-precision human motion capture under different environmental conditions.