Profil

Justus Piater

See author's contact details
Main Referenced Co-authors
Detry, Renaud  (24)
Verly, Jacques  (17)
Jodogne, Sébastien  (12)
Du, Wei  (11)
Hayet, Jean-Bernard (10)
Main Referenced Keywords
machine learning (5); computer vision (3); object tracking in video (2); Approximate Policy Iteration (1); belief propagation (1);
Main Referenced Unit & Research Centers
LUCID-ULiège (1)
Main Referenced Disciplines
Computer science (78)
Engineering, computing & technology: Multidisciplinary, general & others (9)
Architecture (1)
Human health sciences: Multidisciplinary, general & others (1)
Neurosciences & behavior (1)

Publications (total 88)

The most downloaded
1217 downloads
Marée, R., Geurts, P., Piater, J., & Wehenkel, L. (2005). Random Subwindows for Robust Image Classification. In C. Schmid, S. Soatto, ... C. Tomasi (Eds.), Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2005) (pp. 34-40). https://hdl.handle.net/2268/12600

The most cited

189 citations (Scopus®)

Marée, R., Geurts, P., Piater, J., & Wehenkel, L. (2005). Random Subwindows for Robust Image Classification. In C. Schmid, S. Soatto, ... C. Tomasi (Eds.), Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2005) (pp. 34-40). https://hdl.handle.net/2268/12600

Detry, R., Ek, C. H., Madry, M., Piater, J., & Kragic, D. (2012). Generalizing Grasps Across Partly Similar Objects. In IEEE International Conference on Robotics and Automation. doi:10.1109/ICRA.2012.6224992
Peer reviewed

Detry, R., Kraft, D., Kroemer, O., Bodenhagen, L., Peters, J., Krüger, N., & Piater, J. (2011). Learning Grasp Affordance Densities. Paladyn. Journal of Behavioral Robotics, 2 (1), 1-17. doi:10.2478/s13230-011-0012-x
Peer Reviewed verified by ORBi

Piater, J., JODOGNE, S., Detry, R., Kraft, D., Krüger, N., Kroemer, O., & Peters, J. (2011). Learning Visual Representations for Perception-Action Systems. International Journal of Robotics Research, 30 (3), 294-307. doi:10.1177/0278364910382464
Peer Reviewed verified by ORBi

Bodenhagen, L., Detry, R., Piater, J., & Krüger, N. (2011). What a successful grasp tells about the success chances of grasps in its vicinity. In ICDL-EpiRob.
Peer reviewed

Detry, R., & Piater, J. (2011). Grasp Generalization Via Predictive Parts [Paper presentation]. Austrian Robotics Workshop.

Krüger, N., Piater, J., Geib, C., Steedman, M., Wörgötter, F., Ude, A., Asfour, T., & Dillmann, R. (2010). Object-Action Complexes: Grounded Abstractions of Sensorimotor Processes. In 4th International Conference on Cognitive Systems.
Peer reviewed

Detry, R., Kraft, D., Buch, A. G., Krüger, N., & Piater, J. (2010). Refining Grasp Affordance Models by Experience. In IEEE International Conference on Robotics and Automation. doi:10.1109/ROBOT.2010.5509126
Peer reviewed

Detry, R., & Piater, J. (2010). Continuous Surface-point Distributions for 3D Object Pose Estimation and Recognition. In Asian Conference on Computer Vision.
Peer reviewed

Piater, J., Hoyoux, T., & Du, W. (2010). Video analysis for continuous sign language recognition. In 4th Workshop on the Representation and Processing of Sign Languages: Corpora and Sign Language Technologies.
Peer reviewed

Declercq, A., & Piater, J. (2010). Affine Warp Propagation for Fast Simultaneous Modelling and Tracking of Articulated Objects. ACCV10.
Peer reviewed

Dreuw, P., Forster, J., Gweth, Y., Stein, D., Ney, H., Martínez Ruiz, G., Verges Llahí, J., Crasborn, O., Ormel, E., Du, W., Hoyoux, T., Piater, J., Moya Lazaro, J., & Wheatley, M. (2010). SignSpeak -- Scientific Understanding and Vision-Based Technological Development for Continuous Sign Language Recognition and Translation. In 4th Workshop on the Representation and Processing of Sign Languages: Corpora and Sign Language Technologies.
Peer reviewed

Erkan, A., Kroemer, O., Detry, R., Altun, Y., Piater, J., & Peters, J. (2010). Learning Probabilistic Discriminative Models of Grasp Affordances under Limited Supervision. In IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1586-1591). doi:10.1109/IROS.2010.5650088
Peer reviewed

Detry, R., Başeski, E., Popović, M., Touati, Y., Krüger, N., Kroemer, O., Peters, J., & Piater, J. (2010). Learning Continuous Grasp Affordances by Sensorimotor Exploration. In J. Peters & O. Sigaud (Eds.), From Motor Learning to Interaction Learning in Robots. Springer Berlin.

Kroemer, O., Detry, R., Piater, J., & Peters, J. (2010). Grasping with Vision Descriptors and Motor Primitives. In International Conference on Informatics in Control, Automation and Robotics.
Peer reviewed

Dreuw, P., Ney, H., Martínez Ruiz, G., Crasborn, O., Piater, J., Moya Lazaro, J., & Wheatley, M. (2010). The SignSpeak Project -- Bridging the Gap Between Signers and Speakers. In 7th International Conference on Language Resources and Evaluation.
Peer reviewed

Kraft, D., Detry, R., Pugeault, N., Başeski, E., Guerin, F., Piater, J., & Krüger, N. (2010). Development of Object and Grasping Knowledge by Robot Exploration. IEEE Transactions on Autonomous Mental Development, 2 (4), 368-383. doi:10.1109/TAMD.2010.2069098
Peer reviewed

Kroemer, O., Detry, R., Piater, J., & Peters, J. (2010). Adapting Preshaped Grasping Movements using Vision Descriptors. In From Animals to Animats 11 -- International Conference on the Simulation of Adaptive Behavior. doi:10.1007/978-3-642-15193-4_15
Peer reviewed

Kroemer, O., Detry, R., Piater, J., & Peters, J. (2010). Combining Active Learning and Reactive Control for Robot Grasping. Robotics and Autonomous Systems. doi:10.1016/j.robot.2010.06.001
Peer Reviewed verified by ORBi

Piater, J., Jodogne, S., Detry, R., Kraft, D., Krüger, N., Kroemer, O., & Peters, J. (2009). Learning Visual Representations for Interactive Systems. In 14th International Symposium on Robotics Research.
Peer reviewed

Kroemer, O., Detry, R., Piater, J., & Peters, J. (2009). Active Learning using Mean Shift Optimization for Robot Grasping. In IEEE/RSJ International Conference on Intelligent Robots and Systems. doi:10.1109/IROS.2009.5354345
Peer reviewed

Kraft, D., Detry, R., Pugeault, N., Başeski, E., Piater, J., & Krüger, N. (2009). Learning Objects and Grasp Affordances through Autonomous Exploration. In International Conference on Computer Vision Systems.
Peer reviewed

Fritz, M., Schiele, B., & Piater, J. (Eds.). (2009). Computer Vision Systems: Seventh International Conference. Springer.

Detry, R., Pugeault, N., & Piater, J. (2009). A Probabilistic Framework for 3D Visual Object Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence. doi:10.1109/TPAMI.2009.64
Peer Reviewed verified by ORBi

Detry, R., Başeski, E., Krüger, N., Popović, M., Touati, Y., Kroemer, O., Peters, J., & Piater, J. (2009). Learning Object-specific Grasp Affordance Densities. In International Conference on Development and Learning. doi:10.1109/DEVLRN.2009.5175520
Peer reviewed

Piater, J. (2009). Planning Readings: a Comparative Exploration of Basic Algorithms. Computer Science Education, 19 (3), 179-192. doi:10.1080/08993400903255226
Peer Reviewed verified by ORBi

Başeski, E., Pugeault, N., Kalkan, S., Piater, J., & Krüger, N. (2009). Using 3D Contours and Their Relations for Cognitive Vision and Robotics. In 24th International Symposium on Computer and Information Sciences. doi:10.1109/ISCIS.2009.5291815
Peer reviewed

Detry, R., Başeski, E., Krüger, N., Popović, M., Touati, Y., & Piater, J. (2009). Autonomous Learning of Object-specific Grasp Affordance Densities [Paper presentation]. Approaches to Sensorimotor Learning on Humanoid Robots (Workshop at the IEEE International Conference on Robotics and Automation).

Du, W., Hayet, J.-B., Verly, J., & Piater, J. (2009). Ground-Target Tracking in Multiple Cameras Using Collaborative Particle Filters and Principal Axis-Based Integration. IPSJ Transactions on Computer Vision and Applications, 1, 58-71. doi:10.2197/ipsjtcva.1.58
Peer Reviewed verified by ORBi

Du, W., & Piater, J. (2008). A Probabilistic Approach to Integrating Multiple Cues in Visual Tracking. In 10th European Conference on Computer Vision (pp. 225-238). Springer.
Peer reviewed

Declercq, A., & Piater, J. (2008). Online Learning of Gaussian Mixture Models - a Two-Level Approach. In VISAPP 2008: Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1 (pp. 605-611). INSTICC - Institute for Systems and Technologies of Information, Control and Communication.
Peer reviewed

Kraft, D., Başeski, E., Popović, M., Batog, A. M., Kjær-Nielsen, A., Krüger, N., Petrick, R., Geib, C., Pugeault, N., Steedman, M., Asfour, T., Dillmann, R., Kalkan, S., Wörgötter, F., Hommel, B., Detry, R., & Piater, J. (2008). Exploration and Planning in a Three-Level Cognitive Architecture. In International Conference on Cognitive Systems (CogSys).
Peer reviewed

Piater, J., Scalzo, F., & Detry, R. (2008). Vision as Inference in a Hierarchical Markov Network [Paper presentation]. International Conference on Cognitive and Neural Systems.

Piater, J., & Detry, R. (2008). 3D Probabilistic Representations for Vision and Action [Paper presentation]. Robotics Challenges for Machine Learning II.

Detry, R., Pugeault, N., & Piater, J. (2008). Probabilistic Pose Recovery Using Learned Hierarchical Object Models. In International Cognitive Vision Workshop (Workshop at the 6th International Conference on Vision Systems).
Peer reviewed

Demaret, J.-N., Piater, J. (Other coll.), Boigelot, B. (Other coll.), & Leclercq, P. (Other coll.). (2008). Programme SMA Sémantique.

Olszewska, J., Mathes, T., De Vleeschouwer, C., Piater, J., & Macq, B. (2007). Non-Rigid Object Tracker Based On a Robust Combination of Parametric Active Contour and Point Distribution Model. In Proceedings of the SPIE Conference on Visual Communication and Image Processing.
Peer reviewed

Jodogne, S., & Piater, J. (2007). Closed-Loop Learning of Visual Control Policies. Journal of Artificial Intelligence Research, 28, 349-391. doi:10.1613/jair.2110
Peer Reviewed verified by ORBi

Du, W., & Piater, J. (2007). Multi-Camera People Tracking by Collaborative Particle Filters and Principal Axis-Based Integration. In Asian Conference on Computer Vision (pp. 365-374). Springer.
Peer reviewed

Declercq, A., & Piater, J. (2007). On-line Simultaneous Learning and Tracking of Visual Feature Graphs. In 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR07) (pp. 1-6). IEEE Computer Society.
Peer reviewed

Hayet, J.-B., & Piater, J. (2007). On-Line Rectification of Sport Sequences with Moving Cameras. In Mexican International Conference on Artificial Intelligence (pp. 736-746). Springer.
Peer reviewed

Du, W., & Piater, J. (2007). Sequential Variational Inference for Distributed Multi-Sensor Tracking and Fusion. In The 10th International Conference on Information Fusion. doi:10.1109/ICIF.2007.4408026
Peer reviewed

Scalzo, F., & Piater, J. (2007). Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models. In 2nd Beyond Patches Workshop.
Peer reviewed

Detry, R., & Piater, J. (2007). Hierarchical Integration of Local 3D Features for Probabilistic Pose Recovery [Poster presentation]. Robot Manipulation: Sensing and Adapting to the Real World (Workshop at Robotics, Science and Systems).

Jodogne, S., Briquet, C., & Piater, J. (September 2006). Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks. Lecture Notes in Computer Science, 4212, 210-221. doi:10.1007/11871842_23
Peer reviewed

Du, W., & Piater, J. (2006). Multi-view object tracking using sequential belief propagation. In Computer Vision – ACCV 2006 (pp. 684-693). Berlin, Germany: Springer-Verlag Berlin. doi:10.1007/11612032
Peer reviewed

Du, W., & Piater, J. (2006). Data Fusion by Belief Propagation for Multi-Camera Tracking. In The 9th International Conference on Information Fusion. doi:10.1109/ICIF.2006.301712
Peer reviewed

Verly, J., Piater, J., Van Droogenbroeck, M., & Embrechts, J.-J. (2006). Research Unit in Signal and Image Exploitation (INTELSIG).

Desurmont, X., Hayet, J.-B., Delaigle, J.-F., Piater, J., & Macq, B. (2006). TRICTRAC Video Dataset: Public HDTV Synthetic Soccer Video Sequences With Ground Truth. In Workshop on Computer Vision Based Analysis in Sport Environments (CVBASE) (pp. 92-100).
Peer reviewed

Mathes, T., & Piater, J. (2006). Robust Non-Rigid Object Tracking Using Point Distribution Manifolds. In 28th Annual Symposium of the German Association for Pattern Recognition (DAGM) (pp. 515-524). Springer.
Peer reviewed

Du, W., Hayet, J.-B., Piater, J., & Verly, J. (2006). Collaborative Multi-Camera Tracking of Athletes in Team Sports. In Workshop on Computer Vision Based Analysis in Sport Environments (CVBASE) (pp. 2-13).
Peer reviewed

Scalzo, F., & Piater, J. (2006). Unsupervised Learning of Dense Hierarchical Appearance Representations. In International Conference on Pattern Recognition (pp. 395-398). doi:10.1109/ICPR.2006.1144
Peer reviewed

Jodogne, S., & Piater, J. (2006). Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions. Lecture Notes in Computer Science, 4212, 222-233. doi:10.1007/11871842_24
Peer reviewed

Du, W., & Piater, J. (2005). Tracking by cluster analysis of feature points and multiple particle filters. In Pattern Recognition and Image Analysis (pp. 701-710). Berlin, Germany: Springer-Verlag Berlin. doi:10.1007/11552499_77
Peer reviewed

Scalzo, F., & Piater, J. (2005). Apprentissage non-supervisé de hiérarchies de caractéristiques visuelles. In Actes du Congrès ORASIS.
Peer reviewed

Jodogne, S., & Piater, J. (2005). Learning, then Compacting Visual Policies. In 7th European Workshop on Reinforcement Learning (pp. 8-10).
Peer reviewed

Marée, R., Geurts, P., Piater, J., & Wehenkel, L. (2005). Decision Trees and Random Subwindows for Object Recognition. In ICML workshop on Machine Learning Techniques for Processing Multimedia Content (MLMM2005).
Peer reviewed

Gabriel, P. F., Hayet, J.-B., Piater, J., & Verly, J. (2005). Object Tracking Using Color Interest Points.

JODOGNE, S., & Piater, J. (2005). Controlling an Agent by Focusing its Attention on Interactively Selected Patterns. Revue HF : Electronics/Communications, (1), 14-16.
Peer reviewed

Gabriel, P., Piater, J., & Verly, J. (2005). Object tracking using a combined appearance and geometric model. Revue HF : Electronics/Communications, (1), 46.
Peer reviewed

Jodogne, S., Scalzo, F., & Piater, J. (2005). Task-Driven Learning of Spatial Combinations of Visual Features. In Proc. of the IEEE Workshop on Learning in Computer Vision and Pattern Recognition.
Peer reviewed

Jodogne, S., & Piater, J. (2005). Reinforcement Learning of Perceptual Classes using Q Learning Updates. In Proc. of the 23rd IASTED International Conference on Artificial Intelligence and Applications (pp. 445-450). Acta Press.
Peer reviewed

Jodogne, S., & Piater, J. (2005). Apprentissage Interactif de Liaisons Directes entre Perceptions Visuelles et Actions. In Actes du Congrès ORASIS.
Peer reviewed

Gabriel, P., Hayet, J.-B., Piater, J., & Verly, J. (2005). Utilisation des Points d'Intérêts Couleurs pour le Suivi d'Objets. In Actes du Congrès ORASIS.
Peer reviewed

Scalzo, F., & Piater, J. (2005). Statistical Learning of Visual Feature Hierarchies. In Proc. of the IEEE Workshop on Learning in Computer Vision and Pattern Recognition.
Peer reviewed

Jodogne, S., & Piater, J. (2005). Interactive Learning of Mappings from Visual Percepts to Actions. In 22nd International Conference on Machine Learning (pp. 393-400). doi:10.1145/1102351.1102401
Peer reviewed

Gabriel, P., Hayet, J.-B., Piater, J., & Verly, J. (2005). Object Tracking Using Color Interest Points. In International Conference on Advanced Video and Signal based Surveillance (pp. 159-164). doi:10.1109/AVSS.2005.1577260
Peer reviewed

Du, W., & Piater, J. (2005). Tracking by cluster analysis of feature points and multiple particle filters. In 3rd International Conference on Advances in Pattern Recognition (pp. 701-710). Springer.
Peer reviewed

Scalzo, F., & Piater, J. (2005). Unsupervised Learning of Visual Feature Hierarchies. In Proceedings of the International Conference on Machine Learning and Data Mining (MLDM) (pp. 243-252). Springer.
Peer reviewed

Mathes, T., & Piater, J. (2005). Robust Non-Rigid Object Tracking Using Point Distribution Models. In British Machine Vision Conference (pp. 849-858). doi:10.5244/C.19.89
Peer reviewed

Hayet, J.-B., Mathes, T., Czyz, J., Piater, J., Verly, J., & Macq, B. (2005). A Modular Multi-camera Framework for Team Sport Tracking [Paper presentation]. IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2005), Como, Italy.

Scalzo, F., & Piater, J. (2005). Unsupervised learning of visual feature hierarchies. In Machine Learning and Data Mining in Pattern Recognition (pp. 243-252). Berlin, Germany: Springer-Verlag Berlin. doi:10.1007/b138149
Peer reviewed

Hayet, J.-B., Piater, J., & Verly, J. (2005). Fast 2D model-to-image registration using vanishing points for sports video analysis [Paper presentation]. The IEEE International Conference on Image Processing 2005 (ICIP’05), Geona, Italy.

Marée, R., Geurts, P., Piater, J., & Wehenkel, L. (2005). Random Subwindows for Robust Image Classification. In C. Schmid, S. Soatto, ... C. Tomasi (Eds.), Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2005) (pp. 34-40).
Peer reviewed

Marée, R., Geurts, P., Piater, J., & Wehenkel, L. (2005). Biomedical image classification with random subwindows and decision trees. In Computer Vision for Biomedical Image Applications (pp. 220-229). Berlin, Germany: Springer-Verlag Berlin. doi:10.1007/11569541_23
Peer reviewed

Verly, J., & Piater, J. (2004). Image acquisition, processing, and visualization for biomedical applications [Paper presentation]. 4th GIGA Day: Where life sciences and engineering meet: practical aspects.

Verly, J., Piater, J., Van Droogenbroeck, M., & Embrechts, J.-J. (2004). Signal and Image Exploitation at the University of Liège: Strategic Plan and Some Applications [Paper presentation]. Journées d’étude et exposition Optique et Vision Industrielle, Université Catholique de Louvain (UCL), Belgium.

Hayet, J.-B., Piater, J., & Verly, J. (2004). Incremental Rectification of Sports Fields in Video Streams With Application to Soccer. In Advanced Concepts for Intelligent Vision Systems (pp. 1-8).
Peer reviewed

Marée, R., Geurts, P., Piater, J., & Wehenkel, L. (2004). A generic approach for image classification based on decision tree ensembles and local sub-windows. In K.-S. Hong & Z. Zhang (Eds.), Proceedings of the 6th Asian Conference on Computer Vision (pp. 860-865). Asian Federation of Computer Vision Societies (AFCV).
Peer reviewed

Jodogne, S., & Piater, J. (2004). Interactive Selection of Visual Features through Reinforcement Learning. In 24th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (pp. 285-298). Springer.
Peer reviewed

Hayet, J.-B., Piater, J., & Verly, J. (2004). Robust Incremental Rectification of Sports Video Sequences. In Proceedings of the British Machine Vision Conference (pp. 687-696).
Peer reviewed

Gabriel, P. F., Piater, J., & Verly, J. (2004). Object tracking using a combined appearance and geometric model [Paper presentation]. URSI Forum 2004, Academy Palace, Brussels, Belgium.

Crowley, J., & Piater, J. (2004). International Conference on Vision Systems. Machine Vision and Applications, 16 (1).
Peer Reviewed verified by ORBi

Gabriel, P. F., Verly, J., Piater, J., & Genon, A. (2003). The State of the Art in Multiple Object Tracking Under Occlusion in Video Sequences [Paper presentation]. dvanced Concepts for Intelligent Vision Systems (ACIVS 2003), Ghent, Belgium.

Platt, R., Brock, O., Fagg, A., Karuppiah, D., Rosenstein, M., Coelho, J., Huber, M., Piater, J., Wheeler, D., & Grupen, R. (2003). A Framework For Humanoid Control and Intelligence. In Proceedings of the IEEE International Conference on Humanoid Robots.
Peer reviewed

Gabriel, P., Piater, J., & Verly, J. (2003). Tracking of Objects in Video Streams Using Points of Interest. In URSI Forum (pp. 40).
Peer reviewed

Marée, R., Geurts, P., Visimberga, G., Piater, J., & Wehenkel, L. (2003). An empirical comparison of machine learning algorithms for generic image classification. In F. Coenen, A. Preece, ... A. L. Macintosh (Eds.), Proceedings of the 23rd SGAI international conference on innovative techniques and applications of artificial intelligence, Research and development in intelligent systems XX (pp. 169-182). Springer.
Peer reviewed

Gabriel, P., Verly, J., Piater, J., & Genon, A. (2003). The State of the Art in Multiple Object Tracking Under Occlusion in Video Sequences. In Advanced Concepts for Intelligent Vision Systems (pp. 166-173).
Peer reviewed

Crowley, J., Piater, J., Vincze, M., & Paletta, L. (Eds.). (2003). Computer Vision Systems: Third International Conference. Springer.

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