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., & Piater, J. (2011). Grasp Generalization Via Predictive Parts. Paper presented at Austrian Robotics Workshop. |
| 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 |
| 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 |
 | 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 |
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., 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. |
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 |
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 |
| 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 |
| Detry, R., & Piater, J. (2010). Continuous Surface-point Distributions for 3D Object Pose Estimation and Recognition. In Asian Conference on Computer Vision. 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 |
| 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 |
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 |
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 |
| 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 |
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 |
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 |
Detry, R., Başeski, E., Krüger, N., Popović, M., Touati, Y., & Piater, J. (2009). Autonomous Learning of Object-specific Grasp Affordance Densities. Paper presented at Approaches to Sensorimotor Learning on Humanoid Robots (Workshop at the IEEE International Conference on Robotics and Automation). |
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 |
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 |
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 |
| 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 |
| 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 |
Piater, J., Scalzo, F., & Detry, R. (2008). Vision as Inference in a Hierarchical Markov Network. Paper presented at International Conference on Cognitive and Neural Systems. |
Piater, J., & Detry, R. (2008). 3D Probabilistic Representations for Vision and Action. Paper presented at Robotics Challenges for Machine Learning II. |
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 |
Demaret, J.-N., Piater, J. (Other coll.), Boigelot, B. (Other coll.), & Leclercq, P. (Other coll.). (2008). Programme SMA Sémantique. |
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 |
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 |
Detry, R., & Piater, J. (2007). Hierarchical Integration of Local 3D Features for Probabilistic Pose Recovery. Poster session presented at Robot Manipulation: Sensing and Adapting to the Real World (Workshop at Robotics, Science and Systems). |
| 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 |
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 |
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 |
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 |
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 |
Scalzo, F., & Piater, J. (2007). Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models. In 2nd Beyond Patches Workshop. 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 |
| 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 |
Verly, J., Piater, J., Van Droogenbroeck, M., & Embrechts, J.-J. (2006). Research Unit in Signal and Image Exploitation (INTELSIG). |
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 |
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 |
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 |
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 |
| 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. (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 |
Jodogne, S., & Piater, J. (2005). Learning, then Compacting Visual Policies. In 7th European Workshop on Reinforcement Learning (pp. 8-10). Peer reviewed |
Scalzo, F., & Piater, J. (2005). Apprentissage non-supervisé de hiérarchies de caractéristiques visuelles. In Actes du Congrès ORASIS. Peer reviewed |
Hayet, J.-B., Piater, J., & Verly, J. (2005). Fast 2D model-to-image registration using vanishing points for sports video analysis. Paper presented at The IEEE International Conference on Image Processing 2005 (ICIP’05), Geona, Italy. |
| 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 |
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 |
Hayet, J.-B., Mathes, T., Czyz, J., Piater, J., Verly, J., & Macq, B. (2005). A Modular Multi-camera Framework for Team Sport Tracking. Paper presented at IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2005), Como, Italy. |
| 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 |
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 |
Gabriel, P. F., Hayet, J.-B., Piater, J., & Verly, J. (2005). Object Tracking Using Color Interest Points. |
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 |
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 |
| 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 |
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 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). 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 |
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 |
Verly, J., & Piater, J. (2004). Image acquisition, processing, and visualization for biomedical applications. Paper presented at 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 presented at Journées d’étude et exposition Optique et Vision Industrielle, Université Catholique de Louvain (UCL), Belgium. |
| Crowley, J., & Piater, J. (2004). International Conference on Vision Systems. Machine Vision and Applications, 16 (1). Peer Reviewed verified by ORBi |
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 |
Gabriel, P. F., Piater, J., & Verly, J. (2004). Object tracking using a combined appearance and geometric model. Paper presented at URSI Forum 2004, Academy Palace, Brussels, Belgium. |
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 |
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 |
Crowley, J., Piater, J., Vincze, M., & Paletta, L. (Eds.). (2003). Computer Vision Systems: Third International Conference. Springer. |
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 |
| 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., Piater, J., & Verly, J. (2003). Tracking of Objects in Video Streams Using Points of Interest. In URSI Forum (pp. 40). Peer reviewed |
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. F., Verly, J., Piater, J., & Genon, A. (2003). The State of the Art in Multiple Object Tracking Under Occlusion in Video Sequences. Paper presented at dvanced Concepts for Intelligent Vision Systems (ACIVS 2003), Ghent, Belgium. |