“Machine Learning for Graphics” by Hall

  • ©Peter M. Hall



Entry Number: 20


    Machine Learning for Graphics

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    Computer Graphics is increasingly using techniques from Machine  Learning. The trend is motivated by several factors, but the difficulties and expense of modelling is a major driving force. Here ‘modelling’ is used very broadly to include models of reflection (learn the BRDF of a real material), animation (learn the motion of real objects), as well as three-dimensional models (learn to model complex things). Building around a few examples, we will explore the whys and hows of Machine Learning within Computer Graphics. The course  will outline the basics of data-driven modelling, introduce the foundations of probability and statistics, describe some useful distributions, and differentiate between ML and MAP problems. The ideas  are illustrated using examples drawn from previous SIGGRAPHs; we’ll help non-artists to draw, animate traffic flow from sensor data, and model moving trees from video.  

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