S. Bleuler, M. Brack, L. Thiele, and E. Zitzler, Multiobjective genetic programming: reducing bloat using SPEA2, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546), pp.536-543, 2001.
DOI : 10.1109/CEC.2001.934438

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.28.7279

S. Cagnoni, Evolutionary Computer Vision: A Taxonomic Tutorial, 2008 Eighth International Conference on Hybrid Intelligent Systems, pp.1-6, 2008.
DOI : 10.1109/HIS.2008.168

D. Coombs, M. Herman, T. H. Hong, and M. Nashman, Real-time obstacle avoidance using central flow divergence, and peripheral flow, IEEE Transactions on Robotics and Automation, vol.14, issue.1, pp.49-59, 1998.
DOI : 10.1109/70.660840

K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, vol.6, issue.2, pp.182-197, 2002.
DOI : 10.1109/4235.996017

E. Dunn, G. Olague, and E. Lutton, Parisian camera placement for vision metrology, Pattern Recognition Letters, vol.27, issue.11, pp.1209-1219, 2006.
DOI : 10.1016/j.patrec.2005.07.019

M. Ebner, On the evolution of interest operators using genetic programming, Late Breaking Papers at EuroGP'98: the First European Workshop on Genetic Programming, pp.6-10, 1998.

M. Ebner and A. Zell, Evolving a task specific image operator. Evolutionary image analysis, signal processing and telecommunications: First european workshop, EVOIASP, pp.74-89, 1999.

M. Ebner and A. Zell, Centering behavior with a mobile robot using monocular foveated vision, Robotics and Autonomous Systems, vol.32, issue.4, pp.207-218, 2000.
DOI : 10.1016/S0921-8890(99)00127-X

D. Floreano, T. Kato, D. Marocco, and E. Sauser, Coevolution of active vision and feature selection, Biological Cybernetics, vol.90, issue.3, pp.218-228, 2004.
DOI : 10.1007/s00422-004-0467-5

C. Gagné, M. Schoenauer, M. Parizeau, and M. Tomassini, Genetic Programming, Validation Sets, and Parsimony Pressure, Proceedings of EuroGP 2006, pp.109-120, 2006.
DOI : 10.1007/11729976_10

F. Gomez and R. Miikkulainen, Incremental Evolution of Complex General Behavior, Adaptive Behavior, vol.5, issue.3-4, pp.317-342, 1997.
DOI : 10.1177/105971239700500305

B. K. Horn and B. G. Schunck, Determining optical flow, Artificial Intelligence, vol.17, issue.1-3, pp.185-203, 1981.
DOI : 10.1016/0004-3702(81)90024-2

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.185.1651

L. Lacassagne, A. Manzanera, J. Denoulet, and A. Mérigot, High performance motion detection: some trends toward new embedded architectures for vision systems, Journal of Real-Time Image Processing, vol.51, issue.5, pp.127-146, 2009.
DOI : 10.1007/s11554-008-0096-7

URL : https://hal.archives-ouvertes.fr/hal-01131002

Y. Lecun, U. Muller, J. Ben, E. Cosatto, and B. Flepp, Off-road obstacle avoidance through end-to-end learning, Proceedings of the Conference on Neural Information Processing Systems, pp.739-746, 2006.

L. M. Lorigo, R. A. Brooks, and W. E. Grimson, Visually-guided obstacle avoidance in unstructured environments, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97, pp.373-379, 1997.
DOI : 10.1109/IROS.1997.649086

T. Low and G. Wyeth, Learning to avoid indoor obstacles from optical flow, Proceedings of the 2007 Australiasian Conference on Robotics and Automation, pp.1-10, 2007.

B. D. Lucas and T. Kanade, An iterative image registration technique with an application to stereo vision, Proc. DARPA Image Understanding Workshop, pp.121-130, 1981.

D. Marocco and D. Floreano, Active vision and feature selection in evolutionary behavioral systems, From Animals to Animats, vol.7, pp.247-255, 2002.

M. C. Martin, Evolving visual sonar: Depth from monocular images, Pattern Recognition Letters, vol.27, issue.11, pp.1174-1180, 2006.
DOI : 10.1016/j.patrec.2005.07.015

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.1774

J. Michels, A. Saxena, and A. Y. Ng, High speed obstacle avoidance using monocular vision and reinforcement learning, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.593-600, 2005.
DOI : 10.1145/1102351.1102426

URL : http://ai.stanford.edu/~asaxena/rccar/ICML_ObstacleAvoidance.pdf

L. Muratet, S. Doncieux, Y. Brì, and J. Meyer, A contribution to vision-based autonomous helicopter flight in urban environments, Robotics and Autonomous Systems, vol.50, issue.4, pp.195-209, 2005.
DOI : 10.1016/j.robot.2004.09.017

URL : https://hal.archives-ouvertes.fr/hal-01185695

R. C. Nelson and J. Aloimonos, Obstacle avoidance using flow field divergence, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.10, pp.1102-1106, 1989.
DOI : 10.1109/34.42840

G. Olague and C. Puente, Parisian evolution with honeybees for three-dimensional reconstruction, Proceedings of the 8th annual conference on Genetic and evolutionary computation , GECCO '06, pp.191-198, 2006.
DOI : 10.1145/1143997.1144030

O. Pauplin, J. Louchet, E. Lutton, and A. De-la-fortelle, Evolutionary Optimisation for Obstacle Detection and Avoidance in Mobile Robotics, Journal of Advanced Computational Intelligence and Intelligent Informatics, vol.9, issue.6, pp.622-629, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00000495

C. W. Reynolds, An evolved, vision-based model of obstacle avoidance behavior, Artificial Life III, pp.327-346, 1994.

A. Saxena, S. H. Chung, and A. Y. Ng, 3-D Depth Reconstruction from a Single Still Image, International Journal of Computer Vision, vol.35, issue.8, pp.53-69, 2008.
DOI : 10.1007/s11263-007-0071-y

M. Suzuki, Enactive Robot Vision, Adaptive Behavior, vol.425, issue.4, 2007.
DOI : 10.1177/1059712308089183

L. Trujillo and G. Olague, Synthesis of interest point detectors through genetic programming, Proceedings of the 8th annual conference on Genetic and evolutionary computation , GECCO '06, pp.887-894, 2006.
DOI : 10.1145/1143997.1144151

I. Ulrich and I. Nourbakhsh, Appearance-based obstacle detection with monocular color vision, Proceedings of AAAI Conference, pp.866-871, 2000.

J. Walker, S. Garrett, and M. Wilson, Evolving Controllers for Real Robots: A Survey of the Literature, Adaptive Behavior, vol.11, issue.3, pp.179-203, 2003.
DOI : 10.1177/1059712303113003

P. A. Whigham, Grammatically-based genetic programming, Proceedings of the Workshop on Genetic Programming: From Theory to Real-World Applications, pp.33-41, 1995.