K. K. Delibasis, S. V. Georgakopoulos, K. Kottari, V. P. Plagianakos, and I. Maglogiannis, Geodesically-corrected Zernike descriptors for pose recognition in omnidirectional images, Integrated Computer-Aided Engineering, pp.1-15, 2016.
DOI : 10.3233/ica-160511

Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long et al., Caffe, Proceedings of the ACM International Conference on Multimedia, MM '14, pp.675-678, 2014.
DOI : 10.1145/2647868.2654889

M. Oquab, L. Bottou, I. Laptev, and J. Sivic, Is object localization for free? - Weakly-supervised learning with convolutional neural networks, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.685-694, 2015.
DOI : 10.1109/CVPR.2015.7298668

URL : https://hal.archives-ouvertes.fr/hal-01015140

A. Krizhevsky, I. Sutskever, and G. E. Hinton, ImageNet classification with deep convolutional neural networks, Advances in neural information processing systems, pp.1097-1105, 2012.
DOI : 10.1162/neco.2009.10-08-881

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

J. Z. Cheng, D. Ni, Y. H. Chou, J. Qin, C. M. Tiu et al., Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans, Scientific Reports, vol.38, issue.1, 2016.
DOI : 10.1118/1.3528204

Q. Li, W. Cai, X. Wang, Y. Zhou, D. D. Feng et al., Medical image classification with convolutional neural network, 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV), pp.844-848, 2014.
DOI : 10.1109/ICARCV.2014.7064414

H. I. Suk, S. W. Lee, and D. Shen, Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis, NeuroImage, vol.101, pp.569-582, 2014.
DOI : 10.1016/j.neuroimage.2014.06.077

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165842

O. L. Junior, D. Delgado, V. Gonçalves, and U. Nunes, Trainable classifier-fusion schemes: An application to pedestrian detection, 2009 12th International IEEE Conference on Intelligent Transportation Systems, 2009.
DOI : 10.1109/ITSC.2009.5309700

H. Tamimi, H. Andreasson, A. Treptow, T. Duckett, and A. Zell, Localization of mobile robots with omnidirectional vision using Particle Filter and iterative SIFT, Robotics and Autonomous Systems, vol.54, issue.9, pp.758-765, 2006.
DOI : 10.1016/j.robot.2006.04.018

S. K. Hwang, M. Billinghurst, and W. Y. Kim, Local Descriptor by Zernike Moments for Real-Time Keypoint Matching, 2008 Congress on Image and Signal Processing, pp.781-785, 2008.
DOI : 10.1109/CISP.2008.651

H. Zhu, H. Shu, T. Xia, L. Luo, and J. L. Coatrieux, Translation and scale invariants of Tchebichef moments, Pattern Recognition, vol.40, issue.9, pp.2530-2542, 2007.
DOI : 10.1016/j.patcog.2006.12.003

URL : https://hal.archives-ouvertes.fr/inserm-00139337

J. D. Shutler and M. S. Nixon, Zernike Velocity Moments for Description and Recognition of Moving Shapes, Procedings of the British Machine Vision Conference 2001, pp.1-10, 2001.
DOI : 10.5244/C.15.72

Y. Yang and D. Ramanan, Articulated pose estimation with flexible mixtures-of-parts, CVPR 2011, pp.1385-1392, 2011.
DOI : 10.1109/CVPR.2011.5995741

K. Kottari, K. Delibasis, V. Plagianakos, and I. Maglogiannis, Fish-Eye Camera Video Processing and Trajectory Estimation Using 3D Human Models, Artificial Intelligence Applications and Innovations, pp.385-394, 2014.
DOI : 10.1007/978-3-662-44654-6_38

URL : https://hal.archives-ouvertes.fr/hal-01391340

Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner, Gradient-based learning applied to document recognition, Proceedings of the IEEE, pp.2278-2324, 1998.
DOI : 10.1109/5.726791

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

L. Bottou, Stochastic Gradient Descent Tricks, Neural Networks: Tricks of the Trade, pp.421-436, 2012.
DOI : 10.1137/1116025

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

A. Toshev and C. Szegedy, DeepPose: Human Pose Estimation via Deep Neural Networks, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.1653-1660, 2014.
DOI : 10.1109/CVPR.2014.214

URL : http://arxiv.org/abs/1312.4659

K. Kemmotsu, T. Tomonaka, S. Shiotani, Y. Koketsu, and M. Iehara, Recognizing human behaviors with vision sensors in a network robot system, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., pp.274-1279, 2006.
DOI : 10.1109/ROBOT.2006.1641884

Z. Zhou, X. Chen, Y. Chung, Z. He, T. X. Han et al., Activity Analysis, Summarization, and Visualization for Indoor Human Activity Monitoring, IEEE Transactions on Circuits and Systems for Video Technology, vol.18, issue.11, pp.1489-1498, 2008.
DOI : 10.1109/TCSVT.2008.2005612

C. Mei and P. Rives, Single View Point Omnidirectional Camera Calibration from Planar Grids, Proceedings 2007 IEEE International Conference on Robotics and Automation, pp.3945-3950, 2007.
DOI : 10.1109/ROBOT.2007.364084

URL : https://hal.archives-ouvertes.fr/hal-00767674

H. Li and R. Hartley, Plane-Based Calibration and Auto-calibration of a Fish-Eye Camera, ACCV 2006, pp.21-30, 2006.
DOI : 10.1007/11612032_3

S. Shah and J. Aggarwal, Intrinsic parameter calibration procedure for a (high-distortion) fish-eye lens camera with distortion model and accuracy estimation*, Pattern Recognition, vol.29, issue.11, pp.1775-1788, 1996.
DOI : 10.1016/0031-3203(96)00038-6

J. Wei, C. F. Li, S. M. Hu, R. R. Martin, and C. L. Tai, Fisheye video correction. Visualization and Computer Graphics, IEEE Transactions on, issue.10, pp.18-1771, 2012.
DOI : 10.1109/tvcg.2011.130

URL : http://cg.cs.tsinghua.edu.cn/papers/fisheye.pdf

N. Hasler, H. Ackermann, B. Rosenhahn, T. Thormahlen, and H. P. Seidel, Multilinear pose and body shape estimation of dressed subjects from image sets, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.1823-1830, 2010.
DOI : 10.1109/CVPR.2010.5539853

K. Delibasis, V. Plagianakos, and I. Maglogiannis, Refinement of human silhouette segmentation in omni-directional indoor videos, Computer Vision and Image Understanding, vol.128, pp.65-83, 2014.
DOI : 10.1016/j.cviu.2014.06.011

M. Rufli, D. Scaramuzza, and R. Siegwart, Automatic detection of checkerboards on blurred and distorted images, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.3121-3126, 2008.
DOI : 10.1109/IROS.2008.4650703