@conference {12665,
	title = {Moving Object Segmentation and Dynamic Scene Reconstruction Using Two Frames},
	booktitle = {Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP {\textquoteright}05). IEEE International Conference on},
	volume = {2},
	year = {2005},
	month = {2005//18/23},
	pages = {705 - 708},
	keywords = {3D, analysis;, constraints;, dynamic, ego-motion, estimation;, flow, image, images;, independent, INTENSITY, least, mean, median, method;, methods;, model;, MOTION, motion;, moving, object, of, parallax, parallax;, parametric, processing;, reconstruction;, scene, segmentation;, signal, squares, squares;, static, structure;, subspace, surface, translational, two-frame, unconstrained, video},
	doi = {10.1109/ICASSP.2005.1415502},
	author = {Agrawala, Ashok K. and Chellapa, Rama}
}
@conference {18258,
	title = {Nonlinear collusion attacks on independent fingerprints for multimedia},
	booktitle = {Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP {\textquoteright}03). 2003 IEEE International Conference on},
	volume = {5},
	year = {2003},
	month = {2003/04//},
	pages = {V - 664-7 vol.5 - V - 664-7 vol.5},
	abstract = {Digital fingerprinting is a technology for tracing the distribution of multimedia content and protecting them from unauthorized redistribution. Collusion attack is a cost effective attack against digital fingerprinting where several copies with the same content but different fingerprints are combined to remove the original fingerprints. In this paper, we investigate average and nonlinear collusion attacks of independent Gaussian fingerprints and study both their effectiveness and the perceptual quality. We also propose the bounded Gaussian fingerprints to improve the perceptual quality of the fingerprinted copies. We further discuss the tradeoff between the robustness against collusion attacks and the perceptual quality of a fingerprinting system.},
	keywords = {attacks;, average, bounded, collusion, computing;, content, copies;, digital, distribution;, fingerprinted, fingerprinting;, fingerprints;, Gaussian, independent, multimedia, nonlinear, perceptual, quality;, robustness;, watermarking;},
	doi = {10.1109/ICASSP.2003.1200058},
	author = {Zhao,Hong and M. Wu and Wang,Z.J. and Liu,K. J.R}
}
@conference {18261,
	title = {Performance of detection statistics under collusion attacks on independent multimedia fingerprints},
	booktitle = {Multimedia and Expo, 2003. ICME {\textquoteright}03. Proceedings. 2003 International Conference on},
	volume = {1},
	year = {2003},
	month = {2003/07//},
	pages = {I - 205-8 vol.1 - I - 205-8 vol.1},
	abstract = {Digital fingerprinting is a technology for tracing the distribution of multimedia content and protecting them from unauthorized redistribution. Collusion attack is a cost effective attack against digital fingerprinting where several copies with the same content but different fingerprints are combined to remove the original fingerprints. In this paper, we consider average attack and several nonlinear collusion attacks on independent Gaussian based fingerprints, and study the detection performance of several commonly used detection statistics in the literature under collusion attacks. Observing that these detection statistics are not specifically designed for collusion scenarios and do not take into account the characteristics of the newly generated fingerprints under collusion attacks, we propose pre-processing techniques to improve the detection performance of the detection statistics under collusion attacks.},
	keywords = {analysis;, attacks;, based, collusion, content;, DETECTION, digital, fingerprint, fingerprinting;, fingerprints;, Gaussian, identification;, independent, multimedia, performance;, preprocessing, processes;, redistribution;, security;, statistical, statistics;, systems;, techniques;, Telecommunication, unauthorized},
	doi = {10.1109/ICME.2003.1220890},
	author = {Zhao,Hong and M. Wu and Wang,Z.J. and Liu,K. J.R}
}
@conference {14896,
	title = {Finding structurally consistent motion correspondences},
	booktitle = {Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision Image Processing., Proceedings of the 12th IAPR International Conference on},
	volume = {1},
	year = {1994},
	month = {1994/10//},
	pages = {650 -653 vol.1 - 650 -653 vol.1},
	abstract = {Much work on deriving scene structure and motion from features assumes as input a set of tracked image features that share a common 3D motion. Producing this input requires segmenting independent motions, and detecting image features that do not correspond to 3D features, originating instead, for example in occlusion boundaries or specularities. We derive a linear program that tells when a set of tracked points might have come from 3D points that share a single motion, assuming affine motion and bounded error. We can also use linear programming to place conservative bounds on the structure of the scene that corresponds to tracked points. We implement and test this algorithm on real images},
	keywords = {3D, boundaries;, common, consistent, correspondences;, estimation;, features;, image, independent, linear, MOTION, motion;, occlusion, programming;, scene, segmentation;, specularities;, structurally, structure;, tracked},
	doi = {10.1109/ICPR.1994.576388},
	author = {Jacobs, David W. and Chennubhotla,C.}
}
