Publikationer av Hedvig Kjellström

Refereegranskade

Artiklar

[1]

S. Broomé et al., "Going Deeper than Tracking : A Survey of Computer-Vision Based Recognition of Animal Pain and Emotions," International Journal of Computer Vision, vol. 131, no. 2, s. 572-590, 2023.

[2]

F. J. Lawin et al., "Is Markerless More or Less? : Comparing a Smartphone Computer Vision Method for Equine Lameness Assessment to Multi-Camera Motion Capture," Animals, vol. 13, no. 3, 2023.

[3]

A. Maki et al., "In Memoriam : Jan-Olof Eklundh," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 9, s. 4488-4489, 2022.

[4]

S. Broomé et al., "Sharing pain : Using pain domain transfer for video recognition of low grade orthopedic pain in horses," PLOS ONE, vol. 17, no. 3, s. e0263854, 2022.

[5]

T. Kucherenko et al., "Moving Fast and Slow : Analysis of Representations and Post-Processing in Speech-Driven Automatic Gesture Generation," International Journal of Human-Computer Interaction, vol. 37, no. 14, s. 1300-1316, 2021.

[6]

P. Jonell et al., "Multimodal Capture of Patient Behaviour for Improved Detection of Early Dementia : Clinical Feasibility and Preliminary Results," Frontiers in Computer Science, vol. 3, 2021.

[7]

A. Karvonen et al., "The ‘New Urban Science’: towards the interdisciplinary and transdisciplinary pursuit of sustainable transformations," Urban Transformations, vol. 3, no. 1, 2021.

[8]

P. H. Andersen et al., "Towards Machine Recognition of Facial Expressions of Pain in Horses," Animals, vol. 11, no. 6, 2021.

[9]

M. Klasson, C. Zhang och H. Kjellström, "Using Variational Multi-view Learning for Classification of Grocery Items," Patterns, vol. 1, no. 8, 2020.

[10]

C. Zhang et al., "Advances in Variational Inference," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 8, s. 2008-2026, 2019.

[11]

K. Stefanov et al., "Modeling of Human Visual Attention in Multiparty Open-World Dialogues," ACM Transactions on Human-Robot Interaction, vol. 8, no. 2, 2019.

[12]

A. Pieropan et al., "Robust and adaptive keypoint-based object tracking," Advanced Robotics, vol. 30, no. 4, s. 258-269, 2016.

[13]

J. Romero et al., "Extracting Postural Synergies for Robotic Grasping," IEEE Transactions on robotics, vol. 29, no. 6, s. 1342-1352, 2013.

[14]

J. Romero et al., "Non-parametric hand pose estimation with object context," Image and Vision Computing, vol. 31, no. 8, s. 555-564, 2013.

[15]

. Sanmohan et al., "Primitive-Based Action Representation and Recognition," Advanced Robotics, vol. 25, no. 6-7, s. 871-891, 2011.

[16]

H. Kjellström, J. Romero och D. Kragic, "Visual object-action recognition : Inferring object affordances from human demonstration," Computer Vision and Image Understanding, vol. 115, no. 1, s. 81-90, 2011.

[17]

H. Kjellström och O. Engwall, "Audiovisual-to-articulatory inversion," Speech Communication, vol. 51, no. 3, s. 195-209, 2009.

[18]

S. Ahlberg et al., "An information fusion demonstrator for tactical intelligence processing in network-based defense," Information Fusion, vol. 8, no. 1, s. 84-107, 2007.

[19]

O. Engwall et al., "Designing the user interface of the computer-based speech training system ARTUR based on early user tests," Behavior and Information Technology, vol. 25, no. 4, s. 353-365, 2006.

[20]

D. Ormoneit et al., "Representing cyclic human motion using functional analysis," Image and Vision Computing, vol. 23, no. 14, s. 1264-1276, 2005.

[21]

H. Sidenbladh och M. J. Black, "Learning the statistics of people in images and video," International Journal of Computer Vision, vol. 54, no. 2-Jan, s. 181-207, 2003.

Konferensbidrag

[22]

W. Yin et al., "Controllable Motion Synthesis and Reconstruction with Autoregressive Diffusion Models," i 2023 32ND IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION, RO-MAN, 2023, s. 1102-1108.

[23]

S. Broomé et al., "Recur, Attend or Convolve? : On Whether Temporal Modeling Matters for Cross-Domain Robustness in Action Recognition," i 2023 IEEE/CVF WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV), 2023, s. 4188-4198.

[24]

O. Mikheeva et al., "Aligned Multi-Task Gaussian Process," i Proceedings of the 25th International Conference on Artificial Intelligence and Statistics, AISTATS 2022, 2022, s. 2970-2988.

[25]

M. Rashid et al., "Equine Pain Behavior Classification via Self-Supervised Disentangled Pose Representation," i 2022 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2022), 2022, s. 152-162.

[26]

T. Kucherenko et al., "Multimodal analysis of the predictability of hand-gesture properties," i AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022, s. 770-779.

[27]

R. Tu et al., "Optimal transport for causal discovery," i ICLR 2022 : 10th International Conference on Learning Representations, International Conference on Learning Representations, 2022.

[28]

R. Nagy et al., "A Framework for Integrating Gesture Generation Models into Interactive Conversational Agents," i 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS)., 2021.

[29]

R. Nagy et al., "A framework for integrating gesture generation models into interactive conversational agents," i Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, 2021, s. 1767-1769.

[30]

B. Christoffersen et al., "Asymptotically Exact and Fast Gaussian Copula Models for Imputation of Mixed Data Types," i Proceedings of Machine Learning Research, 2021, s. 870-885.

[31]

M. M. Sorkhei, G. E. Henter och H. Kjellström, "Full-Glow : Fully conditional Glow for more realistic image generation," i Pattern Recognition : 43rd DAGM German Conference, DAGM GCPR 2021, 2021, s. 697-711.

[32]

J. Mänttäri et al., "Interpreting Video Features : A Comparison of 3D Convolutional Networks and Convolutional LSTM Networks," i 15th Asian Conference on Computer Vision, ACCV 2020, 2021, s. 411-426.

[33]

T. Kucherenko et al., "Speech2Properties2Gestures : Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech," i IVA '21 : Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents, 2021, s. 145-147.

[34]

M. Rashid, H. Kjellström och Y. J. Lee, "Action Graphs : Weakly-supervised Action Localization with Graph Convolution Networks," i 2020 ieee winter conference on applications of computer vision (wacv), 2020, s. 604-613.

[35]

R. Tu et al., "Causal Discovery in the Presence of Missing Data," i 22nd international conference on artificial intelligence and statistics, vol 89, 2020.

[36]

T. Kucherenko et al., "Gesticulator : A framework for semantically-aware speech-driven gesture generation," i ICMI '20: Proceedings of the 2020 International Conference on Multimodal Interaction, 2020.

[37]

C. Ringqvist et al., "Interpolation in Auto Encoders with Bridge Processes," i Proceedings of the 25th International Conference on Pattern Recognition, ICPR 2020, 2020.

[38]

J. Mänttäri et al., "Interpreting Video Features : A Comparison of 3D Convolutional Networks and Convolutional LSTM Networks," i Asian Conference on Computer Vision, 2020.

[39]

J. Wenger, H. Kjellström och R. Triebel, "Non-Parametric Calibration for Classification," i International Conference on Artificial Intelligence and Statistics, Vol 108, 2020.

[40]

P. L. Dovesi et al., "Real-Time Semantic Stereo Matching," i Proceedings - IEEE International Conference on Robotics and Automation, 2020, s. 10780-10787.

[41]

K. Håkansson et al., "Robot-assisted detection of subclinical dementia : progress report and preliminary findings," i In 2020 Alzheimer's Association International Conference. ALZ., 2020.

[42]

M. Klasson, C. Zhang och H. Kjellström, "A hierarchical grocery store image dataset with visual and semantic labels," i Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019, 2019, s. 491-500.

[43]

T. Kucherenko et al., "Analyzing Input and Output Representations for Speech-Driven Gesture Generation," i 19th ACM International Conference on Intelligent Virtual Agents, 2019.

[44]

S. Eriksson et al., "Dancing with Drones : Crafting Novel Artistic Expressions through Intercorporeality," i Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019, s. 617:1-617:12.

[45]

S. Broomé et al., "Dynamics are important for the recognition of equine pain in video," i Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2019.

[46]

R. Tu et al., "Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation," i Advances in neural information processing systems 32 (NIPS 2019), 2019.

[47]

T. Kucherenko et al., "On the Importance of Representations for Speech-Driven Gesture Generation : Extended Abstract," i International Conference on Autonomous Agents and Multiagent Systems (AAMAS '19), May 13-17, 2019, Montréal, Canada, 2019, s. 2072-2074.

[48]

J. Butepage, H. Kjellström och D. Kragic, "Predicting the what and how - A probabilistic semi-supervised approach to multi-task human activity modeling," i IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2019, s. 2923-2926.

[49]

P. Wolfert et al., "Should Beat Gestures Be Learned Or Designed? : A Benchmarking User Study," i ICDL-EPIROB 2019 : Workshop on Naturalistic Non-Verbal and Affective Human-Robot Interactions, 2019.

[50]

C. Hamesse et al., "Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation," i Proceedings of Machine Learning Research 106, 2019.

[51]

J. Butepage, H. Kjellström och D. Kragic, "Anticipating many futures : Online human motion prediction and generation for human-robot interaction," i 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2018, s. 4563-4570.

[52]

P. Haubro Andersen et al., "Can a Machine Learn to See Horse Pain? : An Interdisciplinary Approach Towards Automated Decoding of Facial Expressions of Pain in the Horse," i Measuring Behavior 2018 - 11th International Conference on Methods and Techniques in Behavioral Research 6-8 June, 2018, 2018.

[53]

O. Mikheeva, C. H. Ek och H. Kjellström, "Perceptual facial expression representation," i Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018, 2018, s. 179-186.

[54]

C. Hamesse et al., "Simultaneous measurement imputation and outcome prediction for achilles tendon rupture rehabilitation," i CEUR Workshop Proceedings, 2018, s. 82-86.

[55]

K. Karipidou et al., "Computer Analysis of Sentiment Interpretation in Musical Conducting," i Proceedings - 12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017, 2017, s. 400-405.

[56]

J. Butepage et al., "Deep representation learning for human motion prediction and classification," i 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), 2017, s. 1591-1599.

[57]

C. Zhang, H. Kjellström och S. Mandt, "Determinantal point processes for mini-batch diversification," i Uncertainty in Artificial Intelligence - Proceedings of the 33rd Conference, UAI 2017, 2017.

[58]

Y. Zhang, J. Beskow och H. Kjellström, "Look but Don’t Stare : Mutual Gaze Interaction in Social Robots," i 9th International Conference on Social Robotics, ICSR 2017, 2017, s. 556-566.

[59]

A. Eriksson och H. Kjellström, "A formal approach to anomaly detection," i ICPRAM 2016 - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods, 2016, s. 317-326.

[60]

S. Caccamo et al., "Active perception and modeling of deformable surfaces using Gaussian processes and position-based dynamics," i IEEE-RAS International Conference on Humanoid Robots, 2016, s. 530-537.

[61]

C. Zhang, S. Mandt och H. Kjellström, "Balanced Population Stochastic Variational Inference," i NIPS Workshop on Advances in Approximate Bayesian Inference, 2016.

[62]

A. Qu et al., "Bridging Medical Data Inference to Achilles Tendon Rupture Rehabilitation," i NIPS Workshop on Machine Learning for Health, 2016.

[63]

C. Zhang et al., "Diagnostic Prediction Using Discomfort Drawing with IBTM," i Machine Learning in Health Care, 2016.

[64]

C. Zhang, H. Kjellström och B. C. Bertilson, "Diagnostic Prediction Using Discomfort Drawings," i NIPS Workshop on Machine Learning for Health, 2016.

[65]

C. Zhang, H. Kjellström och C. H. Ek, "Inter-battery topic representation learning," i Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, s. 210-226.

[66]

A. Pieropan et al., "Robust tracking of unknown objects through adaptive size estimation and appearance learning," i Proceedings - IEEE International Conference on Robotics and Automation, 2016, s. 559-566.

[67]

J. Butepage, H. Kjellström och D. Kragic, "Social Affordance Tracking over Time - A Sensorimotor Account of False-Belief Tasks," i Proceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016, 2016, s. 1014-1019.

[68]

R. Güler et al., "Estimating the Deformability of Elastic Materials using Optical Flow and Position-based Dynamics," i Humanoid Robots (Humanoids), 2015 IEEE-RAS 15th International Conference on, 2015, s. 965-971.

[69]

A. Pieropan et al., "Robust 3D tracking of unknown objects," i Proceedings - IEEE International Conference on Robotics and Automation, 2015, s. 2410-2417.

[70]

A. Pieropan et al., "Audio-Visual Classification and Detection of Human Manipulation Actions," i 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), 2014, s. 3045-3052.

[71]

A. Pieropan, C. H. Ek och H. Kjellström, "Recognizing Object Affordances in Terms of Spatio-Temporal Object-Object Relationships," i Humanoid Robots (Humanoids), 2014 14th IEEE-RAS International Conference on, 2014, s. 52-58.

[72]

A. Pieropan et al., "Robust Tracking through Learning," i 32nd Annual Conference of the Robotics Society of Japan, 2014, 2014.

[73]

A. Pieropan och H. Kjellström, "Unsupervised object exploration using context," i The 23rd IEEE International Symposium on Robot and Human Interactive Communication, 2014 RO-MAN, 2014.

[74]

D. Geronimo och H. Kjellström, "Unsupervised surveillance video retrieval based on human action and appearance," i Proceedings - International Conference on Pattern Recognition, 2014, s. 4630-4635.

[75]

C. Zhang, D. Song och H. Kjellström, "Contextual Modeling with Labeled Multi-LDA," i 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013, s. 2264-2271.

[76]

C. Zhang et al., "Factorized Topic Models," i 1st International Conference on Learning Representations, ICLR 2013, 2-4 May 2013, Scottsdale, United States, 2013.

[77]

A. Pieropan, C. H. Ek och H. Kjellström, "Functional Object Descriptors for Human Activity Modeling," i 2013 IEEE International Conference on Robotics and Automation (ICRA), 2013, s. 1282-1289.

[78]

A. Thippur, C. H. Ek och H. Kjellström, "Inferring hand pose : A comparative study of visual shape features," i 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2013, 2013, s. 6553698.

[79]

M. Hjelm et al., "Sparse Summarization of Robotic Grasping Data," i 2013 IEEE International Conference on Robotics and Automation (ICRA), 2013, s. 1082-1087.

[80]

C. Zhang et al., "Supervised Hierarchical Dirichlet Processes with Variational Inference," i 2013 IEEE International Conference on Computer Vision Workshops (ICCVW), 2013, s. 254-261.

[81]

F. T. Pokorny et al., "Persistent Homology for Learning Densities with Bounded Support," i Advances in Neural Information Processing Systems 25 : 26th Annual Conference on Neural Information Processing Systems 2012, 2012, s. 1817-1825.

[82]

F. T. Pokorny et al., "Topological Constraints and Kernel-Based Density Estimation," i Advances in Neural Information Processing Systems 25, Workshop on Algebraic Topology and Machine Learning, December 8th, Nevada, USA, 2012.

[83]

J. Romero, H. Kjellström och D. Kragic, "Hands in Action : Real-Time 3D Reconstruction of Hands in Interaction with Objects," i 2010 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2010, s. 458-463.

[84]

J. Romero et al., "Spatio-Temporal Modeling of Grasping Actions," i IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010), 2010, s. 2103-2108.

[85]

H. Kjellström, D. Kragic och M. J. Black, "Tracking People Interacting with Objects," i 2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2010, s. 747-754.

[86]

M. Do et al., "Grasp recognition and mapping on humanoid robots," i 9th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS09, 2009, s. 465-471.

[87]

J. Romero, H. Kjellström och D. Kragic, "Modeling and Evaluation of Human-to-Robot Mapping of Grasps," i ICAR : 2009 International Conference on Advanced Robotics, 2009, s. 228-233.

[88]

J. Romero, H. Kjellström och D. Kragic, "Monocular Real-Time 3D Articulated Hand Pose Estimation," i 9th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS09, 2009, s. 87-92.

[89]

J. Romero, H. Kjellström och D. Kragic, "Human-to-Robot Mapping of Grasps," i 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Nice, France. September 22 - 26 2008, 2008.

[90]

H. Kjellström et al., "Simultaneous Visual Recognition of Manipulation Actions and Manipulated Objects," i Computer Vision - Eccv 2008, Pt Ii, Proceedings, 2008, s. 336-349.

[91]

H. Kjellström, J. Romero och D. Kragic, "Visual Recognition of Grasps for Human-to-Robot Mapping," i 2008 IEEE/RSJ International Conference On Robots And Intelligent Systems, Vols 1-3, Conference Proceedings, 2008, s. 3192-3199.

[92]

H. Kjellström et al., "Audio-visual phoneme classification for pronunciation training applications," i INTERSPEECH 2007 : 8TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION, 2007, s. 57-60.

[93]

O. Engwall et al., "Feedback management in the pronunciation training system ARTUR," i Proceedings of CHI 2006, 2006, s. 231-234.

[94]

H. Kjellström, O. Engwall och O. Bälter, "Reconstructing Tongue Movements from Audio and Video," i INTERSPEECH 2006 AND 9TH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING, Vol. 1-5, 2006, s. 2238-2241.

[95]

H. Sidenbladh, P. Svenson och J. Schubert, "Comparing future situation pictures," i 2005 7th International Conference on Information Fusion (FUSION), Vols 1 and 2, 2005, s. 963-968.

[96]

E. Eriksson et al., "Design Recommendations for a Computer-Based Speech Training System Based on End User Interviews," i Proceedings of the Tenth International Conference on Speech and Computers, 2005, s. 483-486.

[97]

J. Schubert och H. Sidenbladh, "Sequential clustering with particle filters - estimating the number of clusters from data," i 2005 7th International Conference on Information Fusion (FUSION), Vols 1 and 2, 2005, s. 122-129.

[98]

J. Grahn och H. Kjellström, "Using SVM for efficient detection of human motion," i 2nd Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, VS-PETS, 2005, s. 231-238.

[99]

O. Bälter et al., "Wizard-of-Oz Test of ARTUR - a Computer-Based Speech Training System with Articulation Correction," i proceedings of ASSETS 2005, 2005, s. 36-43.

[100]

H. Sidenbladh, P. Svenson och J. Schubert, "Comparing multi-target trackers on different force unit levels," i SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION XIII, 2004, s. 306-314.

[101]

H. Sidenbladh, "Detecting human motion with support vector machines," i PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2, 2004, s. 188-191.

[102]

J. Schubert et al., "Methods and system design of the IFD03 information fusion demonstrator," i Ninth International Command and Control Research and Technology Symposium, 2004, s. 1-29.

[103]

S. Ahlberg et al., "The IFD03 information fusion demonstrator," i Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004, 2004, s. 936-943.

[104]

P. Svenson och H. Sidenbladh, "Determining possible avenues of approach using ANTS," i FUSION 2003 : PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE OF INFORMATION FUSION, VOLS 1 AND 2, 2003, s. 1110-1117.

[105]

H. Sidenbladh, "Multi-target particle filtering for the probability hypothesis density," i FUSION 2003 : PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE OF INFORMATION FUSION, VOLS 1 AND 2, 2003, s. 800-806.

[106]

H. Sidenbladh och S.-L. Wirkander, "Tracking random sets of vehicles in terrain," i Proceedings of the 2003 IEEE Workshop on Multi-Object Tracking, 2003.

[107]

H. Sidenbladh, M. J. Black och L. Sigal, "Implicit probabilistic models of human motion for synthesis and tracking," i COMPUTER VISON - ECCV 2002, PT 1, 2002, s. 784-800.

[108]

M. Bray, H. Sidenbladh och J.-O. Eklundh, "Recognition of gestures in the context of speech," i 16th International Conference on Pattern Recognition, 2002. Proceedings., 2002.

[109]

D. Ormoneit et al., "Learning and tracking cyclic human motion," i Advances in Neural Information Processing Systems 13, 2001.

[110]

H. Sidenbladh och M. J. Black, "Learning image statistics for Bayesian tracking," i Proceedings of the IEEE International Conference on Computer Vision, 2001, s. 709-716.

[111]

H. Sidenbladh, F. De la Torre och M. J. Black, "A framework for modeling the appearance of 3D articulated figures," i IEEE International Conference on Automatic Face and Gesture Recognition, 2000.

[112]

D. Ormoneit et al., "Learning and tracking human motion using functional analysis," i IEEE Workshop on Human Modeling, Analysis and Synthesis, 2000.

[113]

D. Ormoneit, H. Sidenbladh och M. J. Black, "Stochastic modeling and tracking of human motion," i Learning 2000, 2000.

[114]

H. Sidenbladh, M. J. Black och D. J. Fleet, "Stochastic tracking of 3D human figures using 2D image motion," i European Conference on Computer Vision, 2000.

[115]

H. Sidenbladh, D. Kragic och H. I. Christensen, "Person following behaviour for a mobile robot," i Proceedings - IEEE International Conference on Robotics and Automation, 1999, s. 670-675.

Kapitel i böcker

[116]

C. Zhang och H. Kjellström, "How to Supervise Topic Models," i Computer Vision - ECCV 2014 Workshops : Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II, Agapito, Bronstein, Rother red., Zurich : Springer Publishing Company, 2014, s. 500-515.

Icke refereegranskade

Konferensbidrag

[117]

S. B. Wang et al., "Multimodal communication error detection for driver-car interaction," i ICINCO 2007: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL RA-1: ROBOTICS AND AUTOMATION, VOL 1, 2007, s. 365-371.

Kapitel i böcker

[118]

H. Kjellström, "Contextual Action Recognition," i Visual Analysis of Humans : Looking at People, T. B. Moeslund, A. Hilton, V. Krüger and L. Sigal red., : Springer, 2011, s. 355-376.

[119]

H. Kjellström, "Datorer som ser människor," i Sinnen, signaler och tolkningar av verkligheten, Lindberg, Bo red., Göteborg : Kungliga vetenskaps- och vitterhetssamhället, 2007.