references.bib

@article{pinker1978representation,
  title={The representation and manipulation of three-dimensional space in mental images},
  author={Pinker, Steven and Kosslyn, Stephen M},
  journal={Journal of Mental Imagery},
  volume={2},
  number={1},
  pages={69--84},
  year={1978},
  publisher={Brandon House.}
}

@article{PauwelsArchitecture,
author = {Pauwels, Karl and Krüger, Norbert and Lappe, Markus and W\"org\"otter, Florentin and Van Hulle, Marc M.}, 
title = {A cortical architecture on parallel hardware for motion processing in real time}, 
volume = {10}, 
number = {10}, 
year = {2010}, 
doi = {10.1167/10.10.18}, 
journal = "Journal of Vision" 
}

@ARTICLE{Gautama_OpticalFlow,
        AUTHOR= "Gautama, T. and {Van Hulle}, M.",
        TITLE= "A phase-based approach to the estimation of the optical flow field using spatial filtering",
        JOURNAL="IEEE Transactions on Neural Networks",
        PAGES="1127-1136",
        YEAR = {2002}
        }

@inproceedings{SuperpixelsSupervoxels,
 author = {Veksler, Olga and Boykov, Yuri and Mehrani, Paria},
 title = {Superpixels and supervoxels in an energy optimization framework},
 booktitle = {Proceedings of the 11th European conference on Computer vision: Part V},
 series = {ECCV 10},
 year = {2010},
 location = {Heraklion, Crete, Greece},
 pages = {211--224},
 numpages = {14},
 acmid = {1888167},
 publisher = {Springer-Verlag},
 address = {Berlin, Heidelberg},
 keywords = {graph cuts, superpixels, supervoxels},
} 

@ARTICLE{Turbopixels,
author={Levinshtein, A. and Stere, A. and Kutulakos, K.N. and Fleet, D.J. and Dickinson, S.J. and Siddiqi, K.},
journal={IEEE Trans. Pattern Anal. Machine Intell.}, 
title={TurboPixels: Fast Superpixels Using Geometric Flows},
year={2009},
month={dec. },
volume={31},
number={12},
pages={2290 -2297},
keywords={Berkeley database;N-cuts;TurboPixels;dense oversegmentation;fast superpixels;geometric flows;image labeling;image segmentation;perceptual grouping;superpixels;computational complexity;geometry;image resolution;image segmentation;},
doi={10.1109/TPAMI.2009.96},
ISSN={0162-8828},}


@book {Pinker_Language,
  title = {The Language Instinct},
  year = {1994},
  publisher = {Harper Perennial Modern Classics},
  organization = {Harper Perennial Modern Classics},
  address = {New York},
  author = {S Pinker}
}


@phdthesis{Sumsi08,
author               = {Sumsi, Miquel~F.},
school               = {Universitat Autonoma de Barcelona},
title                = {Theory and Algorithms on the Median Graph. Application to Graph-based Classification and Clustering},
year                 = {2008},
}      


@ARTICLE{Gordon_1993, 
author={Gordon, N.J. and Salmond, D.J. and Smith, A F M}, 
journal={Radar and Signal Processing, IEE Proceedings F}, 
title={Novel approach to nonlinear/non-Gaussian Bayesian state estimation}, 
year={1993}, 
month={Apr}, 
volume={140}, 
number={2}, 
pages={107-113}, 
keywords={Bayes methods;Kalman filters;filtering and prediction theory;state estimation;tracking;Gaussian noise;algorithm;bearings only tracking problem;bootstrap filter;extended Kalman filter;measurement model;nonGaussian Bayesian state estimation;nonlinear Bayesian state estimation;random samples;recursive Bayesian filters;simulation;state transition model;state vector density}, 
ISSN={0956-375X},}

@inproceedings{Aksoy2010,
  author               = {Aksoy, E.~E. and Abramov, A. and W\"org\"otter, F. and Dellen, B.},
  booktitle            = {ICRA},
  month                = {may},
  pages                = {398--405},
  title                = {Categorizing object-action relations from semantic scene graphs},
  year                 = {2010},
}

@article{Aksoy2011,
  author               = {Aksoy, E.~E. and Abramov, A. and D\"orr, J. and Ning, K. and Dellen, B. and W\"org\"otter, F.},
  journal              = {The International Journal of Robotics Research},
  number               = {10},
  pages                = {1229--1249},
  title                = {Learning the semantics of object-action relations by observation},
  volume               = {30},
  year                 = {2011},
}

@INPROCEEDINGS{Choi_IROS2013, 
author={Changhyun Choi and Christensen, H.I.}, 
booktitle={Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on}, 
title={RGB-D object tracking: A particle filter approach on GPU}, 
year={2013}, 
month={Nov}, 
keywords={feature extraction;graphics processing units;image colour analysis;image sequences;image texture;maximum likelihood estimation;object tracking;particle filtering (numerical methods);pose estimation;rendering (computer graphics);solid modelling;3D points feature;6-DOF object pose tracking;GPU;PCL;RGB-D object tracking;RGB-D sequence;a priori 3D mesh model;colors feature;degrees-of-freedom;geometric feature;graphics processing unit;object rendering;parallelized likelihood evaluation;particle filter approach;photometric feature;red-green-blue depth;surface normals feature;synthetic sequence;texture buffers;Cameras;Graphics processing units;Image color analysis;Rendering (computer graphics);Robots;Solid modeling;Three-dimensional displays}, 
doi={10.1109/IROS.2013.6696485}, 
ISSN={2153-0858},}


@INPROCEEDINGS{Koo_IROS2013, 
author={Seongyong Koo and Dongheui Lee and Dong-Soo Kwon}, 
booktitle={Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on}, 
title={Multiple object tracking using an RGB-D camera by hierarchical spatiotemporal data association}, 
year={2013}, 
month={Nov}, 
keywords={cameras;image colour analysis;object tracking;HSTA;RGB-D camera;RGB-D point set data;component-level spatio-temporal associations;falsely detected object correction;hierarchical spatiotemporal data association;multiple object tracking;red-green-blue-depth camera;Image edge detection;Intelligent robots;Object tracking;Robustness;Spatiotemporal phenomena;Target tracking}, 
doi={10.1109/IROS.2013.6696489}, 
ISSN={2153-0858},}

@article{Kulvicius2012,
   author={Kulvicius, T. and Ning, K. J. and Tamosiunaite, M. and W{\"o}rg{\"o}tter, F.},
   title="Joining movement sequences: {M}odified dynamic movement primitives for robotics applications exemplified on handwriting",
   journal="IEEE Trans. Robot.",
   year="2012",
   volume={28},
   number={1},
   pages={145--157}
}


@INPROCEEDINGS{Rossman_ICRA2014,
  title={Active Learning of Manipulation Sequences},
  author={Rossmann, J{\"u}rgen and Wantia, Nils and Aksoy, Eren Erdal and Haller, Simon and Piater, Justus},
  booktitle={Robotics and Automation (ICRA) 2014. IEEE International Conference on}, 
  year={2014}
}

@INPROCEEDINGS{Kuffner_ICRA2004, 
author={Kuffner, J.J.}, 
booktitle={Robotics and Automation (ICRA) 2004. IEEE International Conference on}, 
title={Effective sampling and distance metrics for 3D rigid body path planning}, 
year={2004}, 
month={April}, 
keywords={Lie groups;interpolation;path planning;sampling methods;3D rigid body path planning;Lie group;SE(3) group;configuration space;distance metrics;interpolation techniques;motion planning algorithms;robots;sampling function;sampling methods;Geophysics computing;Interpolation;Kinematics;Orbital robotics;Path planning;Proteins;Quaternions;Sampling methods;Satellites;Topology}, 
doi={10.1109/ROBOT.2004.1308895}, 
ISSN={1050-4729},}

@INPROCEEDINGS{Buch_CVPR2014, 
author = "Buch, {Anders Glent} and Yang Yang and Norbert Krüger and Petersen, {Henrik Gordon}",
booktitle={Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on},
title = "In Search of Inliers: 3D Correspondence by Local and Global Voting",
year={2014}, 
month={June}, 
}
@ARTICLE{SLICCompared,
author={Achanta, R. and Shaji, A. and Smith, K. and Lucchi, A. and Fua, P. and S{\"u}sstrunk, S.},
journal={IEEE Trans. Pattern Anal. Machine Intell.}, 
title={SLIC Superpixels Compared to State-of-the-Art Superpixel Methods},
year={2012},
month={nov. },
volume={34},
number={11},
pages={2274 -2282},
keywords={SLIC superpixels;computer vision;image boundary;k-means clustering approach;memory efficiency;segmentation performance;simple linear iterative clustering;superpixel generation;supervoxel generation;computer vision;image segmentation;iterative methods;pattern clustering;},
doi={10.1109/TPAMI.2012.120},
ISSN={0162-8828},}

@INPROCEEDINGS{HistogramIntersection, 
author={Barla, A. and Odone, F. and Verri, A.}, 
booktitle={Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on}, 
title={Histogram intersection kernel for image classification}, 
year={2003}, 
month={sept.},  
number={}, 
pages={ III - 513-16 vol.2}, 
keywords={ color properties; histogram intersection kernel; illumination properties; image classification; statistical learning paradigm; support vector machines; image classification; image colour analysis; support vector machines;}, 
doi={10.1109/ICIP.2003.1247294}, 
ISSN={1522-4880},}


@inproceedings{DASP,
author={Weikersdorfer, D. and Gossow, D. and Beetz, M.}, 
booktitle={Pattern Recognition (ICPR), 2012 21st International Conference on}, 
title={Depth-adaptive superpixels}, 
year={2012}, 
pages={2087-2090}, 
keywords={graph theory;image colour analysis;image segmentation;spectral analysis;3D geometry;DASP;RGB-D images;depth-adaptive superpixels;image segmentation algorithms;pixel oversegmentation technique;spectral graph theory;state-of-the-art oversegmentation;uniform distribution;visible surface;Cameras;Clustering algorithms;Geometry;Image color analysis;Image edge detection;Image segmentation;Runtime}, 
ISSN={1051-4651},
}

@INPROCEEDINGS{RusuFPFH, 
author={Rusu, R.B. and Blodow, N. and Beetz, M.}, 
booktitle={Robotics and Automation, 2009. ICRA '09. IEEE International Conference on}, 
title={Fast Point Feature Histograms (FPFH) for 3D registration}, 
year={2009}, 
month={May}, 
pages={3212-3217}, 
keywords={Clouds;Computational complexity;Convergence;Histograms;Intelligent systems;Iterative closest point algorithm;Optimization methods;Performance analysis;Robotics and automation;Robustness}, 
}

@book{kandel2000principles,
  title={Principles of neural science},
  author={Kandel, Eric R and Schwartz, James H and Jessell, Thomas M and others},
  volume={4},
  year={2000},
  publisher={McGraw-Hill New York},
  pages={492-509}
}

@book{piaget1967,
  title={The child's conception of space},
  author={Piaget, J. and Inhelder, B.},
  year={1967},
  publisher={W.W. Norton},
  address={New York}
}

@inproceedings{Galasso2013,
  title={A unified video segmentation benchmark: Annotation, metrics and analysis},
  author={Galasso, Fabio and Nagaraja, Naveen Shankar and C{\'a}rdenas, Tatiana Jim{\'e}nez and Brox, Thomas and Schiele, Bernt},
  booktitle={Computer Vision (ICCV), 2013 IEEE International Conference on},
  year = {2013}
}

@inproceedings{Martinez2014,
 author = {Martinez, D. and Alenya, G. and Jimenez, P. and Torras, C. and Rossmann, J. and Wantia, N. and Aksoy, E. E. and Haller, S. and Piater, J.},
 booktitle = {IEEE Int Conf Robotics and Automation (ICRA)},
 title = {Active learning of manipulation sequences},
 year = {2014},
}

@inproceedings{Schou2012,
 author = {Schou, C. and Car{\o}e, C. F. and Hvilsh{\o}j, M. and Damgaard, J. S. and B{\o}gh, S. and Madsen, O.},
 booktitle = {AAU Workshop on Human-Centered Robotics},
 title = {Human assisted instructing of autonomous industrial mobile manipulator and its qualitative assessment},
 pages = {22--28},
 year = {2012},
}

@inproceedings{Butler2012,
  title={Shake'n'sense: reducing interference for overlapping structured light depth cameras},
  author={Butler, D Alex and Izadi, Shahram and Hilliges, Otmar and Molyneaux, David and Hodges, Steve and Kim, David},
  booktitle={Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems},
  pages={1933--1936},
  year={2012},
  organization={ACM}
}

@inproceedings{Collins1985,
 author = {Collins, K. and Palmer, A.~J. and Rathmill, K.}, 
 booktitle = {Robot technology and applications (Robotics Europe Conference)},
 title = {The Development of a {European} benchmark for the comparison of assembly robot programming systems},
 pages = {187--199},
 year = {1985},
}

@INPROCEEDINGS{MTT_JPDA, 
author={Fortmann, T.E. and Bar-Shalom, Y. and Scheffe, M.}, 
booktitle={Decision and Control including the Symposium on Adaptive Processes, 1980 19th IEEE Conference on}, 
title={Multi-target tracking using joint probabilistic data association}, 
year={1980}, 
month={Dec}, 
volume={19}, 
pages={807-812}, 
keywords={Acoustic measurements;Acoustic sensors;Acoustic signal detection;Clutter;Event detection;Fasteners;Particle measurements;Personal digital assistants;Sea measurements;Target tracking}, 
}

@article{Condensation98,
year={1998},
journal={International Journal of Computer Vision},
volume={29},
number={1},
title={CONDENSATION—Conditional Density Propagation for Visual Tracking},
publisher={Kluwer Academic Publishers},
author={Isard, Michael and Blake, Andrew},
pages={5-28},
language={English},
}

@INPROCEEDINGS{MultiMixtureTracking03, 
author={Vermaak, J. and Doucet, Arnaud and Perez, P.}, 
booktitle={Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on}, 
title={Maintaining multimodality through mixture tracking}, 
year={2003}, 
month={Oct}, 
pages={1110-1116 vol.2}, 
keywords={Bayes methods;Monte Carlo methods;computer vision;image sequences;object detection;recursive estimation;target tracking;Bayesian sequential estimation;Monte Carlo methods;aircraft tracking;face tracking;mixture tracking;mixture weights;mobile robot;nonGaussian models;nonparametric mixture model;particle filters;posterior multimodality;target distributions;tracking recursion;video sequence;Bayesian methods;Computer vision;Filtering;Laser radar;Monte Carlo methods;Particle filters;Radar tracking;Recursive estimation;Target tracking;Video sequences}, 
}

@INPROCEEDINGS{TrackMultTargets01, 
author={Schulz, D. and Burgard, W. and Fox, D. and Cremers, A.B.}, 
booktitle={Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on}, 
title={Tracking multiple moving targets with a mobile robot using particle filters and statistical data association}, 
year={2001}, 
month={}, 
volume={2}, 
pages={1665-1670 vol.2}, 
keywords={feature extraction;filtering theory;laser ranging;mobile robots;object recognition;probability;state estimation;target tracking;feature extraction;joint probabilistic data association filters;laser ranging;mobile robot;multiple moving target tracking;occlusions;particle filters;state estimation;statistical data association;Computer science;Humans;Mobile computing;Mobile robots;Object detection;Particle filters;Particle tracking;Robot sensing systems;State estimation;Target tracking}, 
}


@ARTICLE{MCMCPartFilt_05, 
author={Zia Khan and Balch, T. and Dellaert, F.}, 
journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on}, 
title={MCMC-based particle filtering for tracking a variable number of interacting targets}, 
year={2005}, 
month={Nov}, 
volume={27}, 
number={11}, 
pages={1805-1819}, 
keywords={Markov processes;Monte Carlo methods;filtering theory;sampling methods;target tracking;Markov chain Monte Carlo sampling step;Markov random field motion;interacting targets;multitarget filter;particle filtering;Animals;Computer vision;Filtering;Insects;Markov random fields;Monte Carlo methods;Particle filters;Particle tracking;Sampling methods;Target tracking;Index Terms- Particle filters;Markov chain Monte Carlo.;Markov random fields;multitarget tracking;Algorithms;Animals;Artificial Intelligence;Computer Simulation;Humans;Image Enhancement;Image Interpretation, Computer-Assisted;Information Storage and Retrieval;Markov Chains;Models, Biological;Models, Statistical;Monte Carlo Method;Motion;Movement;Pattern Recognition, Automated;Subtraction Technique;Video Recording}, 
}

@ARTICLE{ApproxMultiTrack_06, 
author={Lanz, O.}, 
journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on}, 
title={Approximate Bayesian multibody tracking}, 
year={2006}, 
month={Sept}, 
volume={28}, 
number={9}, 
pages={1436-1449}, 
keywords={Bayes methods;Markov processes;approximation theory;hidden feature removal;image processing;particle filtering (numerical methods);target tracking;Bayesian multibody tracking;Markov random field approximation;hybrid joint-separable filter;multiple targets;occlusion reasoning;particle filter;visual tracking;Approximation algorithms;Bayesian methods;Computational efficiency;Computational modeling;Inference algorithms;Markov random fields;Particle filters;Particle tracking;Robustness;Target tracking;Bayes filter;Computer vision;approximate inference;occlusion;particle filter.;tracking}, 
}

@incollection{RobustVTMT_06,
year={2006},
booktitle={Computer Vision – ECCV 2006},
volume={3954},
series={Lecture Notes in Computer Science},
editor={Leonardis, Aleš and Bischof, Horst and Pinz, Axel},
doi={10.1007/11744085_9},
title={Robust Visual Tracking for Multiple Targets},
publisher={Springer Berlin Heidelberg},
author={Cai, Yizheng and Freitas, Nando and Little, JamesJ.},
pages={107-118}
}

@article{DetTrackMultiHumans_07,
year={2007},
issn={0920-5691},
journal={International Journal of Computer Vision},
volume={75},
number={2},
title={Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors},
publisher={Springer US},
keywords={human detection; human tracking; AdaBoost},
author={Wu, Bo and Nevatia, Ram},
pages={247-266},
language={English}
}


@ARTICLE{MultipersonTBD_011, 
author={Breitenstein, M.D. and Reichlin, F. and Leibe, B. and Koller-Meier, E. and Van Gool, L.}, 
journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on}, 
title={Online Multiperson Tracking-by-Detection from a Single, Uncalibrated Camera}, 
year={2011}, 
month={Sept}, 
volume={33}, 
number={9}, 
pages={1820-1833}, 
keywords={hidden feature removal;image classification;image motion analysis;object detection;object tracking;particle filtering (numerical methods);traffic engineering computing;video cameras;complex scenes;continuous confidence;generic object category knowledge;graded observation model;high-confidence detection;instance specific information;monocular uncalibrated camera;occlusion;online multiperson tracking by detection;online trained instance specific classifier;particle filtering;pedestrian detectors;Cameras;Detectors;Gaussian distribution;Heuristic algorithms;Motion analysis;Object detection;Target tracking;Multi-object tracking;detector confidence;detector confidence particle filter;online learning;particle filtering;pedestrian detection;sequential Monte Carlo estimation;sports analysis;surveillance;tracking-by-detection;traffic safety.}, 
}


@ARTICLE{SonarMultiTrack_83, 
author={Fortmann, Thomas E. and Bar-Shalom, Y. and Scheffe, M.}, 
journal={Oceanic Engineering, IEEE Journal of}, 
title={Sonar tracking of multiple targets using joint probabilistic data association}, 
year={1983}, 
month={Jul}, 
volume={8}, 
number={3}, 
pages={173-184}, 
keywords={Kalman filtering;Poisson distributions;Sonar tracking;Acoustic sensors;Acoustic signal detection;Clutter;Density measurement;Personal digital assistants;Sea measurements;Sonar applications;Sonar measurements;State estimation;Target tracking}, 
}


@ARTICLE{MultiTrack_79, 
author={Reid, D.B.}, 
journal={Automatic Control, IEEE Transactions on}, 
title={An algorithm for tracking multiple targets}, 
year={1979}, 
month={Dec}, 
volume={24}, 
number={6}, 
pages={843-854}, 
keywords={Bayes procedures;Tracking;Air traffic control;Clustering algorithms;Land vehicles;Marine vehicles;Military aircraft;Probability;Radar detection;Radar tracking;Sea measurements;Target tracking}, 
}