%0 Generic %D 2014 %T Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions %A Andrei Barbu %A Daniel Barrett %A Wei Chen %A N. Siddharth %A Caiming Xiong %A Jason J. Corso %A Christiane D. Fellbaum %A Catherine Hanson %A Stephen José Hanson %A Sebastien Helie %A Evguenia Malaia %A Barak A. Pearlmutter %A Jeffrey Mark Siskind %A Thomas Michael Talavage %A Ronnie B. Wilbur %X

We had human subjects perform a one-out-of-six class action recognition task from video stimuli while undergoing functional magnetic resonance imaging (fMRI). Support-vector machines (SVMs) were trained on the recovered brain scans to classify actions observed during imaging, yielding average classification accuracy of 69.73% when tested on scans from the same subject and of 34.80% when tested on scans from different subjects. An apples-to-apples comparison was performed with all publicly available software that implements state-of-the-art action recognition on the same video corpus with the same cross-validation regimen and same partitioning into training and test sets, yielding classification accuracies between 31.25% and 52.34%. This indicates that one can read people’s minds better than state-of-the-art computer-vision methods can perform action recognition.

%8 09/2014 %2

http://hdl.handle.net/1721.1/100176