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Chimpanzee faces in the wild: Log-euclidean CNNs for predicting identities and attributes of primates

: Freytag, A.; Rodner, E.; Simon, M.; Loos, A.; Kühl, H.S.; Denzler, J.


Rosenhahn, B.:
Pattern recognition. Proceedings : 38th German conference, GCPR 2016, Hannover, Germany, September 12-15, 2016
Berlin: Springer, 2016 (Lecture Notes in Computer Science (LNCS) 9796)
ISBN: 978-3-319-45885-4
ISBN: 978-3-319-45886-1
German Conference on Pattern Recognition (GCPR) <38, 2016, Hannover>
Conference Paper
Fraunhofer IDMT ()

In this paper, we investigate how to predict attributes of chimpanzees such as identity, age, age group, and gender. We build on convolutional neural networks, which lead to significantly superior results compared with previous state-of-the-art on hand-crafted recognition pipelines. In addition, we show how to further increase discrimination abilities of CNN activations by the Log-Euclidean framework on top of bilinear pooling. We finally introduce two curated datasets consisting of chimpanzee faces with detailed meta-information to stimulate further research. Our results can serve as the foundation for automated large-scale animal monitoring and analysis.