Approximate Bayesian image interpretation using generative probabilistic graphics programs

Advances in Neural Information Processing Systems

Volumn , Issue , 2013, Pages

  Mansinghka, Vikash K ^a,b   Kulkarni, Tejas D ^a,b   Perov, Yura N ^a,b,c   Tenenbaum, Joshua B ^a,b  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c SIBERIAN FEDERAL UNIVERSITY   (Russian Federation)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; INVERSE PROBLEMS; STOCHASTIC SYSTEMS; THREE DIMENSIONAL COMPUTER GRAPHICS;

APPROXIMATE BAYESIAN; AUTOMATIC INFERENCE; BAYESIAN INFERENCE; GENERATIVE MODEL; GRAPHICS PROGRAMS; IMAGE INTERPRETATION; PROBABILISTIC PROGRAMMING; REAL-WORLD IMAGE;

STOCHASTIC MODELS;

EID: 84898942632     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. José Manuel Álvarez, Theo Gevers, and Antonio M Lopez. "3D scene priors for road detection". In: Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on. IEEE. 2010, pp. 57-64.
2. Mohamed Aly. "Real time detection of lane markers in urban streets". In: Intelligent Vehicles Symposium, 2008 IEEE. IEEE. 2008, pp. 7-12.
3. Paul Dagum and Michael Luby. "An optimal approximation algorithm for Bayesian inference". In: Artificial Intelligence 93.1 (1997), pp. 1-27.
4. L Del Pero et al. "Bayesian geometric modeling of indoor scenes". In: Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE. 2012, pp. 2719-2726.
5. Andreas Geiger, Philip Lenz, and Raquel Urtasun. "Are we ready for autonomous driving? The KITTI vision benchmark suite". In: Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE. 2012, pp. 3354-3361.
6. Noah Goodman, Vikash Mansinghka, Daniel Roy, Keith Bonawitz, and Joshua Tenenbaum. "Church: A language for generative models". In: UAI. 2008.
7. Geoffrey E Hinton, Simon Osindero, and Yee-Whye Teh. "A fast learning algorithm for deep belief nets". In: Neural computation 18.7 (2006), pp. 1527-1554.
8. Derek Hoiem, Alexei A Efros, and Martial Hebert. "Putting objects in perspective". In: Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on. Vol. 2. IEEE. 2006, pp. 2137-2144.
9. Derek Hoiem, Alexei A Efros, and Martial Hebert. "Recovering surface layout from an image". In: International Journal of Computer Vision 75.1 (2007), pp. 151-172.
10. Berthold Klaus Paul Horn. Robot vision. the MIT Press, 1986.
11. Yann LeCun and Yoshua Bengio. "Convolutional networks for images, speech, and time series". In: The handbook of brain theory and neural networks 3361 (1995).
12. Paul Marjoram, John Molitor, Vincent Plagnol, and Simon Tavaré. "Markov chain Monte Carlo without likelihoods". In: Proceedings of the National Academy of Sciences 100.26 (2003).
13. Greg Mori and Jitendra Malik. "Recognizing objects in adversarial clutter: Breaking a visual CAPTCHA". In: Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on. Vol. 1. IEEE. 2003, pp. I-134.
14. Javier Portilla and Eero P Simoncelli. "A parametric texture model based on joint statistics of complex wavelet coefficients". In: International Journal of Computer Vision 40.1 (2000).
15. Oliver Ratmann, Christophe Andrieu, CarstenWiuf, and Sylvia Richardson. "Model criticism based on likelihood-free inference, with an application to protein network evolution". In: 106.26 (2009), pp. 10576-10581.
16. Ray Smith. "An overview of the Tesseract OCR engine". In: Ninth International Conference on Document Analysis and Recognition. Vol. 2. IEEE. 2007, pp. 629-633.
17. Zhuowen Tu, Xiangrong Chen, Alan L Yuille, and Song-Chun Zhu. "Image parsing: Unifying segmentation, detection, and recognition". In: International Journal of Computer Vision 63.2 (2005), pp. 113-140.
18. Zhuowen Tu and Song-Chun Zhu. "Image Segmentation by Data-Driven Markov Chain Monte Carlo". In: IEEE Trans. Pattern Anal. Mach. Intell. 24.5 (May 2002).
19. Richard D Wilkinson. "Approximate Bayesian computation (ABC) gives exact results under the assumption of model error". In: arXiv preprint arXiv:0811.3355 (2008).
20. David Wingate, Noah D Goodman, A Stuhlmueller, and J Siskind. "Nonstandard interpretations of probabilistic programs for efficient inference". In: Advances in Neural Information Processing Systems 23 (2011).
21. Alan Yuille and Daniel Kersten. "Vision as Bayesian inference: analysis by synthesis?" In: Trends in cognitive sciences 10.7 (2006), pp. 301-308.
22. Yibiao Zhao and Song-Chun Zhu. "Image Parsing via Stochastic Scene Grammar". In: Advances in Neural Information Processing Systems. 2011.