Title | Seeing is worse than believing: Reading people’s minds better than computer-vision methods recognize actions |
Publication Type | Book Chapter |
Year of Publication | 2014 |
Authors | Barbu, A, Barrett, D, Chen, W, Siddharth, N, Xiong, C, Corso, JJ, Fellbaum, CD, Hanson, C, Hanson, SJosé, Helie, S, Malaia, E, Pearlmutter, BA, Siskind, JMark, Talavage, TMichael, Wilbur, RB |
Book Title | Computer Vision – ECCV 2014, Lecture Notes in Computer Science |
Series Title | 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V |
Volume | 8693 |
Pagination | 612–627 |
Publisher | Springer International Publishing |
City | Zurich, Switzerland |
Abstract | 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. |
DOI | 10.1007/978-3-319-10602-1_40 |
Short Title | Computer Vision – ECCV 2014 |
Research Area:
CBMM Relationship:
- CBMM Funded