Smart Animation Tools

Abstract

This chapter discusses the inherent limitations in conventional animation techniques and possible solutions through optimisation and machine learning paradigms. For example, going beyond pre–recorded animation libraries towards more intelligent self-learning models. These models present a range of difficulties in real-world solutions, such as, computational cost, flexibility, and most importantly, artistic control. However, as we discuss in this chapter, advancements in massively parallel processing power and hybrid models provides a transitional medium for these solutions (best of both worlds). We review trends and state of the art techniques and their viability in industry. A particular area of active animation is self–driven characters (i.e., agents mimic the real-world through physics-based models). We discuss and debate each techniques practicality in solving and overcoming current and future limitations.