2 PhD candidates deep learning of activities in video

The primary goal of the two PhD projects is to perform cutting edge research in computer vision and deep learning to automatically detect activities in a multi-camera streaming video environment. Activities will be enriched by person and object detection to arrive at precise descriptions. Relevant research questions are: How can we automatically detect and track activities, as well as persons and objects, in cluttered scenes? What are the underlying mechanisms for spatiotemporal reasoning in video that improve activity detection? How can we enable activity detection and scene understanding from overlapping and non-overlapping (first-person) camera viewpoints? The work is executed as part of the IARPA DIVA research program, together with SRI International, the University of Michigan and the University of Washington. The positions are based at the University of Amsterdam and we expect that candidates are willing to attend yearly project meetings in the USA.

Employer: University of Amsterdam

Expiration date: Friday, March 30, 2018

More information: http://bit.ly/diva2-uva

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