Working thesis title: Captured Life: the creative potential of hybrid realities

Supervisors: Associate Professor Katrina Sluis (primary supervisor), Dr Anna Madeleine Raupach (chair), Dr Baden Pailthorpe

My practice-led PhD project investigates the characteristics of the synthetic, computer-generated image and its intersection with the “indexical” technology of motion capture. In the emerging field of three-dimensional, photorealistic computer simulations, there is little research about the hybridity resulting from the introduction of data captured from real and specific human gestures. Shaped by economic imperatives and software affordances, the computer-generated (CG) image tends towards shiny surfaces and broadly recognisable bodies. Meanwhile, high-end motion capture technology seeks to accurately capture the particular spatial coordinates of multiple human joints and muscle groups for detailed digital reproductions of human motion in three dimensions. The conjunction of these two technologies within motion capture animation opens up a range of questions about the role of humans vis-à-vis machines in the field of computer images.
    The key question for my project concerns the possibilities and limitations of this hybrid process and image output: using human movement as a form of agency, is this a collaboration between humans and machines that reveals the open-ended plasticity of supposedly fixed realities? Or, alternatively, is it another instance in the history of human motion acting as supplement to the logic of the machine, this time in the production lines of algorithmic capitalism? I investigate this question through a historical and practical analysis of both technologies. I create CG images that explore their features and malleability, and reflect upon the politics and internal logics of the 3D software used to make them. I combine these creations with the use of motion capture to record my own human gestures as someone who labours on synthetic images. Additionally, I plan to undertake fieldwork to use motion capture in collaboration with dancers and other movement specialists to explore if and how the effectiveness of human gesture is transformed through the process of datafication and transfer to 3D models.