Some Selected Papers

Mobile Robots

• Constraint-Based Visual Robotic Systems(ICIMS 95)
• A Stereoscopic Visually Guided Mobile Robot(Hawaii International Conference on System Sciences, 96)
• Robot Partners(1st Cooperative Distributed Vision Workshop)
• Interpreting stereo vision for a mobile robot
  To appear in a special issue of Autonomous Robots, 2000.
• Identifying Stereo Corners for Mobile Robot Localization(IROS'98)
• Vision-based Mapping with Cooperative Robots(SPIE'98)
• Cooperative Robot Localization with Vision-based Mapping(ICRA'98).
• Tracking Color Objects in Real Time(M.Sc. Thesis for Vladimir Kravtchenko)
• Efficient Color Object Segmentation Using the Dichromatic Reflection Model(IEEE PACRIM '99)
• Vision-based Mobile Robot Localization and Mapping using Scale-Invariant Features, Proceedings of IEEE International Conference on Robotics and Automation, ICRA 2001, pages 2051-2058, Seoul, Korea, May 2001.
• Local and Global Localization for Mobile Robot using Visual Landmarks, for Intl. Conf. on Intelligent Robots and Systems, November, 2001, pages 414--420.
• Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Landmarks, Intl. Journal of Robotics Research, Vol. 21, No. 8, August 2002, pp. 735--758.
• A Distributed Robot Control Architecture for Guiding a Vision-based Mobile Robot, AAAI Spring Symposium: Intelligent Distributed and Embedded Systems, March 2002.
• Waiting with Jose, a vision-based mobile robot, IEEE International Conference on Robotics and Automation, May 2002
• Global Localization using Distinctive Visual Features Stephen Se, David Lowe and James J. Little, Intl. Conf. on Intelligent Robots and Systems, November, 2002.
• Vision-based Mapping with Backward Correction Stephen Se, David Lowe and James J. Little, Intl. Conf. on Intelligent Robots and Systems, November, 2002.
• Robot-human interaction in a message delivery system (HOMER: Human Oriented Messenger Robot), AAAI Spring Symposium on Human Interaction with Autonomous Systems in Complex Environments, March 2003.
• Patchlets: representing stereo vision data with surface elements Don Murray and James J. Little, WACV 2005, Colorado
• Segmenting correlation stereo range images using surface elements, Don Murray and James J. Little, presented at 3DPVT 2004, Thessaloniki, Greece
• sigmaMCL: Monte-Carlo Localization for Mobile Robots with Stereo Vision P.Elinas and James J. Little, Robotics: Science and Systems, Boston, MA, USA, June 2005
• Vision-based SLAM using the Rao-Blackwellised Particle Filter Robert Sim, Pantelis Elinas, Matt Griffin, and James J. Little, IJCAI-05 Workshop: Reasoning with Uncertainty in Robotics (RUR-05), Edinburgh, July 30, 2005, pages 9--16.
• sigmaSLAM: Stereo Vision SLAM using the Rao-Blackwellised Particle Filter and a Novel Mixture Proposal Distribution Pantelis Elinas, Rob Sim and James J. Little, IEEE ICRA 2006.
• Scalable Vision-based FastSLAM for planetary rovers Robert Sim, Matt Griffin, Alex Shyr, and James J. Little, IROS Workshop on Robot Vision for Space Applications, August 2005, pages 16--21.
• Design and analysis of a framework for real-time vision-based SLAM using Rao-Blackwellised particle filters Robert Sim, Pantelis Elinas, Matt Griffin, Alex Shyr and James J. Little, Computer and Robot Vision 2006, Quebec, June 2006 (Winner of the ``Best Robotics Paper'' award)
• Autonomous vision-based exploration and mapping using hybrid maps and Rao-Blackwellised particle filters Robert Sim and James J. Little. Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), Beijing, 2006. Nominated for best paper.
• Object Discovery using Motion, Appearance and Shape Tristram Southey and James J. Little, Cognitive Robotics Workshop, AAAI 2006.
• Autonomous vision-based exploration and mapping using hybrid maps and Rao-Blackwellised particle filters, Robert Sim and James J. Little. Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), Beijing, 2006. Nominated for best paper.
• Maps, Places, and Worlds, James J. Little. Workshop "From Features to Actions", ICRA 2007, Rome
• Surface Signature-Based Method for Modeling and Recognizing Free-Form Objects Hossein Darbandi, Mabo Ito, James J. Little, 3rd International Symposium on Visual Computing, 2007
• Stereo vision SLAM: Near real-time learning of 3D point-landmark and 2D occupancy-grid maps using particle filters Pantelis Elinas and James J. Little, VSLAM07 Workshop at IROS07
• Learning Qualitative Spatial Relations for Object Classification Tristram Southey and James J. Little, in From Sensors to Human Spatial Concepts, IROS 2007 Workshop,
• The UBC Semantic Robot Vision System Scott Helmer, David Meger, Per-Erik Forssén, Tristram Southey, Sancho McCann, Pooyan Fazli, Jim Little, and David Lowe, (abstract) AAAI 2007
• Curious George: An Attentive Semantic Robot David Meger, Per-Erik Forssen, Kevin Lai, Scott Helmer, Sancho McCann, Tristram Southey, Matthew Baumann, James J. Little, David G. Lowe, and Bruce Dow, in From Sensors to Human Spatial Concepts, IROS 2007 Workshop
• Informed Visual Search: Combining Attention and Object Recognition David Meger, Per-Erik Forssen, Kevin Lai, Scott Helmer, James J. Little, and David G. Lowe, ICRA 08
• Automated Spatial-Semantic Modeling with Applications to Place Labeling and Informed Search Pooja Viswanathan, David Meger, Tristram Southey, James J. Little, Alan Mackworth, Computer and Robot Vision 2009, pages 284--291.
• Viewpoint Detection Models for Sequential Embodied Object Category Recognition, David Meger, Ankur Gupta and James J. Little, ICRA 2010, Anchorage.
• Automated Place Classification using Object Detection Pooja Viswanathan, Tristram Southey, James Little, Alan Mackworth, to appear in CRV2010
• Curious George: An Integrated Visual Search Platform, David Meger, Marius Muja, Scott Helmer, Ankur Gupta, Catherine Gamroth, Tomas Hoffman, Matthew Baumann, Tristram Southey, Pooyan Fazli, Walter Wohlkinger, Pooja Viswanathan, James J. Little, David G. Lowe, and James Orwell, to appear in CRV2010

Robots, Visibility, Motion Planning

• Dynamic Visibility Checking for Vision-Based Motion Planning Simon Leonard and Elizabeth A. Croft and James J. Little, ICRA 08
• Trajectory Specification via Sparse Waypoints for Eye-In-Hand Robots requiring Continuous Target Visibility Ambrose Chan, Elizabeth A. Croft, and James J. Little, ICRA 08
• Two-Fingered Grasp Planning for Randomized Bin-Picking Donna C. Dupuis, Simon Leonard, Matthew A. Baumann, Elizabeth A. Croft and James Little, Robotics: Science and Systems Workshop on Robot Manipulation (RSS08-Manipulation).
• Occlusion-Free Path Planning with a Probabilistic Roadmap, Matthew A. Baumann, Donna C. Dupuis, Simon Leonard, Elizabeth A. Croft and James Little, IROS 08

Recognizing Motion

• Describing Motion for RecognitionJames J. Little and Jeff Boyd (IEEE Symposium on Computer Vision, Coral Gables, Florida, November, 1995, pp. 235--240)
• Global versus Structured Interpretation of Motion: Moving Light Displays(Jeff Boyd and James J. Little) (Non-rigid and Articulated Motion Workshop, CVPR-97)
• Shape of Motion and the Perception of Human GaitsJeff Boyd and James J. Little (Workshop on Empirical Evaluation in Computer Vision, CVPR 98, June 21-22, 1998)
• Recognizing People by Their Gait: the Shape of Motion(in MIT Press Journal Videre. The Web page referenced here contains the abstract, the paper in PDF format and the online demo)
• Representation and Recognition of Complex Human MotionJesse Hoey and James J. Little, (IEEE Conf. on Computer Vision and Pattern Recognition, 2000)
• Probabilistic clustering of optical flow fieldsJesse Hoey and James J. Little, ICCV 2003, Oct. 13, 2003.
• Decision Theoretic Learning of Human Facial DisplaysJesse Hoey and James J. Little, NIPS workshop on Cognitive Vision, Dec. 2003
• Decision Theoretic Modeling of Human Facial DisplaysJesse Hoey and James J. Little, ECCV 2004, May 2004.
• Value Directed Learning of Gestures and Facial DisplaysJesse Hoey and James J. Little, CVPR 2004, June 2004.

Spatio-temporal Databases: Hockey, Tracking

• Video Retrieval by Spatial and Temporal Structure of Trajectories James J. Little and Zhe Gu, (SPIE Storage and Retrieval for Media Databases 2001, San Jose)
• Automatic Acquisition of Motion Trajectories: Tracking Hockey PlayersOkuma, K., Little, J. J., Lowe, D. G., Internet Imaging V, SPIE 2004
• Automatic rectification of long image sequencesOkuma, K., Little, J. J., Lowe, D. G., the Asian Conference on Computer Vision(ACCV), Jeju Island, Korea, January 2004
• A Boosted Particle Filter: Multitarget Detection and TrackingOkuma, K., Taleghani, A., De Freitas, N., Little, J. J., Lowe, D. G., the European Conference on Computer Vision(ECCV), May 2004 (Winner of the "Best Paper in Cognitive Vision" Prize)
• Robust Visual Tracking for Multiple Targets, ECCV May, 2006. Yizheng Cai, Nando de Freitas and James J. Little, Robust Visual Tracking for Multiple Targets, ECCV May, 2006.
• Simultaneous Tracking and Action Recognition using the PCA-HOG Descriptor Wei-Lwun Lu and James J. Little, Simultaneous Tracking and Action Recognition using the PCA-HOG Descriptor, CRV 2006, Quebec, June 2006
• Tracking and Action Recognition at a Distance Wei-Lwun Lu and James J. Little, Tracking and Action Recognition at a Distance, CVBASE '06 - Workshop on Computer Vision Based Analysis in Sport Environments, at ECCV 2006 , Graz, Austria, May 12, 2006
• A Linear Programming Approach for Multiple Object Tracking Hao Jiang, Sid Fels and James J. Little, CVPR07
• Tracking and Recognizing Actions of Multiple Hockey Players using the Boosted Particle Filter Wei-Lwun Lu, Kenji Okuma, and James J. Little , Image and Vision Computing, 27(1-2):189-205, 2009.
• Identifying Players in Broadcast Sports Videos using Conditional Random Fields Wei-Lwun Lu, Jo-Anne Ting, Kevin P. Murphy, and James J. Little, IEEE Conference on Computer Vision and Pattern Recognition (CVPR '11), 2011. To Appear.

Lidar Analyis - Bare Earth

• Deforestation: Extracting 3D Bare-Earth Surface from Airborne LiDAR Data Wei-Lwun Lu, James J. Little, Alla Sheffer, and Hongbo Fu (The Fifth Canadian Conference on Computer and Robot Vision (CRV '08), Windsor, Canada, May 2008. )
• A Hybrid Conditional Random Field for Estimating the Underlying Ground Surface from Airborne LIDAR DataWei-Lwun Lu, Kevin Murphy, James J. Little, Alla Sheffer, Hongbo Fu, IEEE Transactions on Geoscience and Remote Sensing. To Appear.

Computer Vision Languages

• OpenVL: A Novel Software Architecture for Computer Vision Changsong Shen, Sidney Fels, and James J. Little, 3rd IEEE Workshop on Embedded Computer Vision, CVPR07

3D Object Signatures

• Clustered Signatures for Modeling and Recognizing 3D Rigid Objects Hossein Darbandi, Mabo Ito, James J. Little, CVISP'08 - 5th International Conference on Computer Vision, Image and Signal Processing

Terrain Modeling

• Structural Lines, TINs, and DEMs(Spatial Data Handling '98)PDF version
• Structural Lines for Triangulations of Terrain(Workshop on Applications of Computer Vision, 98)PDF Version
• Structural Lines, TINs and DEMs(Algorithmica, Special Issue on Algorithms for Geographical Information, Vol. 30, 2(2001), pp.243-263.)
• Deforming Surface Features Lines in Intrinsic Coordinates--Postscript
  Deforming Surface Features Lines in Intrinsic Coordinates--html version of slides(International Conference on Pattern Recognition, 2000)
• Ordering points for incremental TIN construction from DEMs(Geoinformatica)

Parallel Architectures for Machine Perception

• Computational Architectures for Responsive Vision: the Vision Engine(Computer Architectures for Machine Perception 91)
• Vision Servers and Their Clients(invited paper, (International Conference on Pattern Recognition, 1994)

Stereo and Optical Flow

• Accurate Early Detection of Discontinuities (Vision Interface 92)
• A Smart Buffer for Tracking Using Motion Data (Computer Architectures for Machine Perception 93)

Shape Recovery

• Reflectance and Shape from Image Sequence of a Rotating Object(Vision Interface, 95)
• Reflectance Function Estimation and Shape Recovery from Image Sequence of a Rotating Object(Intl. Conf. on Computer Vision, 95)
• Surface and Shading Model from a Rotating Object
• Wire-frame and Surface Recovery(IEEE Conf. on Computer Vision and Pattern Recognition, 96)
• Geometric and Photometric Constraints for Surface Recovery
• Photometric Stereo and Locality Sensitive High-Dimension Hashing Lin Zhong and James J. Little, CRV, Victoria, BC, 2005