CLASSIFICATION OF VISUAL EFFECTS FOR COMPUTER GRAPHICS, ANIMATION AND MULTIMEDIA

The article is devoted to the study and classification of visual effects used in computer graphics, animation and multimedia in order to create a unified terminological and methodological framework.The development of digital technologies and innovative design techniques leads to the emergence of new techniques in the creation of visual effects.However, their diversity complicates the proper selection of effects for practical tasks, which is important for effective interaction between researchers and practitioners in the fields of graphic design and creative industries.The article proves the relevance of developing a unified terminological and methodological framework for characterising visual effects -both those currently in use and those that can be created through the implementation of digital technologies and tools, as well as innovative design techniques.The purpose of the study is to develop a hierarchical classification system for visual effects based on the established criteria, in particular, the criterion of 'creation technology', the criterion of 'variability' (static or dynamic characteristics) and the additional criterion of 'dimensionality' (2D or 3D appearance).For this purpose, a method of sequential hierarchical classification was applied, which allowed us to divide the effects into three main categories: practical special effects, combined visual effects and computer-generated visual effects.The analysis includes a breakdown of each category by group, species, subspecies and type, which helps to identify distinguishing features and establish relationships between different groups of visual effects.The main results of the study demonstrate that the developed classification contributes to a more structured approach to the use of visual effects in filmmaking, advertising, interactive multimedia projects and other industries.The classification allows optimising the process of selecting effects, increasing their efficiency and adapting them to the latest technologies, taking into account the potential use of artificial neural network algorithms for its further clustering and improvement.