Prof Watson's presentation on making machine learning fun and fast

IBM RTP recently invited Prof Watson to give a presentation on his collaborative research with them.

Making ML Training Fun and Fast
February 27, 2018 @ 2p - 3pm

Prof Watson's collaboration uses interfaces based on manual classification — qualitative coding — to make training of automated machine learning classifiers more engaging and productive. Ultimately, the collaboration will use large touch displays to approximate qualitative coding's data displays.

Adam Marrs publishes on multiview rendering

Student Adam Marrs presented his paper Real-Time View Independent Rasterization for Multi-View Rendering at Eurographics 2017 in Lyon, France! 

Real-Time View Independent Rasterization for Multi-View Rendering
Adam Marrs, Benjamin Watson, and Christopher G. Healey

Proc. Eurographics 2017 short papers, April 25, Lyon, France.

Abstract
Existing graphics hardware parallelizes view generation poorly, placing many multi-view effects – such as soft shadows, defocus blur, and reflections – out of reach for real-time applications. We present emerging solutions that address this problem using a high density point set tailored per frame to the current multi-view configuration, coupled with relatively simple reconstruction kernels. Points are a more flexible rendering primitive, which we leverage to render many high resolution views in parallel. Preliminary results show our approach accelerates point generation and the rendering of multi-view soft shadows up to 9x.

Prof Watson's recent presentation on location experience at NC State's Geospatial Analytics Center

NC State's Geospatial Analytics Center recently invited Prof Watson to give a talk. It went well; at least his hosts said that the audience interacted more with him than any other presentation yet!

Location Experience: Where We’ve Been, Are, and May Be
September 1, 2016 @ 3:30 pm - 4:30 pm

Finding our way has always been necessary, and we have always tried to make it easier. Yet today, wayfinding is changing so rapidly that it makes our heads spin. What have we lost? What might we gain? I will use a review of wayfinding past, present and future to raise such questions; arguing that the enjoyment we experience along the way is now just as important as the efficiency with which we find the way’s end.