PUBLICATIONS

Publications mui


iros2014

Inspection of Pole-Like Structures Using a Vision-Controlled VTOL UAV and Shared Autonomy

Abstract

We present an approach for the inspection of vertical pole-like infrastructure using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structures, such as light and power distribution poles, is a time consuming, dangerous and expensive task with high operator workload. To address these issues, we propose a VTOL platform that can operate at close-quarters, whilst maintaining a safe stand-off distance and rejecting environmental disturbances. We adopt an Image based Visual Servoing (IBVS) technique using only two line features to stabilise the vehicle with respect to a pole. Visual, inertial and sonar data are used, making the approach suitable for indoor or GPS-denied environments. Results from simulation and outdoor flight experiments demonstrate the system is able to successfully inspect and circumnavigate a pole.

 

 Sa, S. Hrabar, and P. Corke, “Inspection of pole-like structures using a vision-controlled VTOL UAV and shared autonomy,” in Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference pp. 4819–4826, Sept 2014.

iros2014

Simultaneous Localisation and Planning on Multiple Map Hypotheses

Simultaneous Localization and Planning on Multiple Map Hypotheses

Abstract
This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.
T. Morris, F. Dayoub, P. Corke, and B. Upcroft, “Simultaneous localization and planning on multiple hypotheses,” in Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference pp. 4531–4536, Sept 2014
ICRA2014

Vision based guidance for robot navigation in agriculture

 Vision based guidance for robot navigation in agriculture

Abstract
This paper describes a novel vision based texture tracking method to guide autonomous vehicles in agricultural fields where the crop rows are challenging to detect. Existing methods require sufficient visual difference between the crop and soil for segmentation, or explicit knowledge of the structure of the crop rows. This method works by extracting and tracking the direction and lateral offset of the dominant parallel texture in a simulated overhead view of the scene and hence abstracts away crop-specific details such as colour, spacing and periodicity. The results demonstrate that the method is able to track crop rows across fields with extremely varied appearance during day and night. We demonstrate this method can autonomously guide a robot along the crop rows.
A. R. English, P. Ross, D. Ball, and P. Corke, “Vision based guidance for robot navigation in agriculture Proc. IEEE Int. Conf. Robotics and Automation, pp. 1693–1698, 2014
ICRA2014

Empirical modelling of rolling shutter effect

Abstract
We propose and evaluate a novel methodology to identify the rolling shutter parameters of a real camera. We also present a model for the geometric distortion introduced when a moving camera with a rolling shutter views a scene. Unlike previous work this model allows for arbitrary camera motion, including accelerations, is exact rather than a linearization and allows for arbitrary camera projection models, for example fisheye or panoramic. We show the significance of the errors introduced by a rolling shutter for typical robot vision problems such as structure from motion, visual odometry and pose estimation.
ACRA2014

Text recognition approaches for indoor robotics : a comparison

Text recognition approaches for indoor robotics : a comparison

O. Lam, F. Dayoub, R. Schulz, and P. Corke, “Text recognition approaches for indoor robotics : a compari in Australasian Conference on Robotics & Automation (ACRA2014), (University of Melbourne, Melbo VIC), December 2014

Our researchers make their work generally available in various forms such as:

Since the conception of the Centre in 2014, over 90 affiliated journal articles and conference proceedings have been published.

2015

Conference Papers

  • Aftab, K., & Hartley, R. (2015). Convergence of Iteratively Re-weighted Least Squares to Robust M-Estimators. Paper presented at the IEEE Winter Conference on Applications of Computer Vision (WACV), 2015, Los Alamitos, CA, USA.
  • Aftab, K., & Hartley, R. (2015). LQ-bundle adjustment. Paper presented at the IEEE International Conference on Image Processing (ICIP) 2015.
  • Ajanthan, T., Hartley, R., Salzmann, M., & Li, H. (2015). Iteratively Reweighted Graph Cut for Multi-label MRFs with Non-convex Priors. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  • Bewley, A., & Upcroft, B. (2015). From ImageNet to mining: Adapting visual object detection with minimal supervision. Paper presented at the Field and Service Robotics (FSR) 2015, University of Toronto, Canada.
  • Buyu, L., Xuming, H., & Gould, S. (2015). Multi-class Semantic Video Segmentation with Exemplar-Based Object Reasoning. Paper presented at the IEEE Winter Conference on Applications of Computer Vision (WACV), 2015.
  • Chamberlain, W., Drummond, T., & Corke, P. (2015). Distributed Robotic Vision as a Service. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015, Canberra, Australia.
  • Chen, Z., Lowry, S., Jacobson, A., Ge, Z., & Milford, M. (2015). Distance Metric Learning for Feature-Agnostic Place Recognition. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, Hamburg, Germany.
  • Chen, Z., Lowry, S., Jacobson, A., Ge, Z., & Milford, M. (2015). Distance metric learning for feature-agnostic place recognition. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.
  • Cunningham-Nelson, S., Moghadam, P., Roberts, J., & Elfes, A. (2015). Coverage-Based Next Best View Selection. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.
  • Dansereau, D. G., Williams, S. B., & Corke, P. I. (2015). Closed-Form Change Detection from Moving Light Field Cameras. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.
  • Dayoub, F., Dunbabin, M., & Corke, P. (2015). Robotic Detection and Tracking of Crown-of-Thorns Starfish. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, Hamburg, Germany.
  • Eich, M. (2015). Towards Fuzzy Knowledge Based Scene Understanding from RGB-D Images. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  • Faraki, M., Harandi, M. T., & Porikli, F. (2015). Material Classification on Symmetric Positive Definite Manifolds. Paper presented at the IEEE Winter Conference on Applications of Computer Vision (WACV), 2015, Los Alamitos, CA, USA. http://dx.doi.org/10.1109/WACV.2015.105
  • Fernando, B., Gavves, E., Muselet, D., & Tuytelaars, T. (2015). Learning to rank based on subsequences. Paper presented at the International Conference on Computer Vision (ICCV) 2015.
  • Fernando, B., Gavves, E., Oramas, J., Ghodrati, A., & Tuytelaars, T. (2015). Modeling video evolution for action recognition. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
  • Gamage, D., & Drummond, T. (2015). Reduced Dimensionality Extended Kalman Filter for SLAM. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.
  • Ge, Z., McCool, C., Sanderson, C., & Corke, P. (2015). Subset feature learning for fine-grained category classification. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Piscataway, NJ, USA.
  • Hall, D., McCool, C., Dayoub, F., Sunderhauf, N., & Upcroft, B. (2015). Evaluation of Features for Leaf Classification in Challenging Conditions. Paper presented at the IEEE Winter Conference on Applications of Computer Vision (WACV), 2015, Los Alamitos, CA, USA.
  • Hanxi, L., Yi, L., & Porikli, F. (2015). Robust online visual tracking with a single convolutional neural network. Paper presented at the Asian Conference on Computer Vision (ACCV) 1-5 Nov. 2014, Cham, Switzerland.
  • Ila, V., Polok, L., Solony, M., Smrz, P., & Zemcik, P. (2015). Fast Covariance Recovery in Incremental Nonlinear Least Square Solvers. Paper presented at the IEEE International Conference on Robotics and Automation (ICRA), 2015, Seattle.
  • Jacobson, A., Chen, Z., Rallabandi, V. R., & Milford, M. (2015). Multi-Scale Place Recognition with Multi-Scale Sensing. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.
  • Jacobson, A., Zetao, C., & Milford, M. (2015). Online place recognition calibration for out-of-the-box SLAM. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, Piscataway, NJ, USA.
  • Jia, X., Gavves, S., Fernando, B., & Tuytelaars, T. (2015). Guided long-short term memory for image caption generation. Paper presented at the International Conference on Computer Vision (ICCV) 2015.
  • Leitner, J. (2015). Extending Visual Perception With Haptic Exploration for Improved Scene Understanding. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  • Leitner, J., Dansereau, D. G., Shirazi, S., & Corke, P. (2015). The Need for Dynamic & Active Datasets. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Massachusetts, USA.
  • Liao, Z., & Carneiro, G. (2015). The use of deep learning features in a hierarchical classifier learned with the minimization of a non-greedy loss function that delays gratification. Paper presented at the IEEE International Conference on Image Processing (ICIP) 2015.
  • Lin, G., Shen, C., Reid, I., & Hengel, A. v. d. (2015). Deeply Learning the Messages in Message Passing Inference. Paper presented at the Neural Information Processing Systems (NIPS), 2015, Montreal, Canada.
  • Lui, V., & Drummond, T. (2015). Image based optimisation without global consistency for constant time monocular visual SLAM. Paper presented at the IEEE International Conference on Robotics and Automation (ICRA), 2015, Piscataway, NJ, USA.
  • Lui, V., Gamage, D., & Drummond, T. (2015). Fast Inverse Compositional Image Alignment with Missing Data and Re-weighting. Paper presented at the British Machine Vision Conference (BMVC) 2015, Swansea, UK.
  • Maire, F., Alvarez, L. M., & Hodgson, A. (2015). Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach. Paper presented at the AI 2015: Advances in Artificial Intelligence.
  • Malti, A., Bartoli, A., & Hartley, R. (2015). A Linear Least-Squares Solution to Elastic Shape-from-Template. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  • Marouchos, A., Muir, B., Babcock, R., & Dunbabin, M. (2015). A shallow water AUV for benthic and water column observations. Paper presented at the MTS/IEEE OCEANS, 2015, Piscataway, NJ, USA.
  • McMahon, S., Sünderhauf, N., Milford, M., & Upcroft, B. (2015). TripNet: Detecting Trip Hazards on Construction Sites. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.
  • McMahon, S., Sünderhauf, N., Upcroft, B., & Milford, M. (2015). How Good Are EdgeBoxes, Really. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  • Milford, M., Shen, C., Lowry, S., Suenderhauf, N., Shirazi, S., Lin, G., . . . Upcroft, B. (2015). Sequence Searching with Deep-learnt Depth for Condition-and Viewpoint-invariant Route-based Place Recognition. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  • Ok, K., Gamage, D., Drummond, T., Dellaert, F., & Roy, N. (2015). Monocular image space tracking on a computationally limited MAV. Paper presented at the IEEE International Conference on Robotics and Automation (ICRA), 2015.
  • Paisitkriangkrai, S., Sherrah, J., Janney, P., & Van-Den Hengel, A. (2015). Effective semantic pixel labelling with convolutional networks and conditional random fields. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Piscataway, NJ, USA.
  • Pepperell, E., Corke, P. I., & Milford, M. J. (2015). Automatic image scaling for place recognition in changing environments. Paper presented at the IEEE International Conference on Robotics and Automation (ICRA), 2015, Piscataway, NJ, USA.
  • Pham, T. T., Reid, I., Latif, Y., & Gould, S. (2015). Hierarchical Higher-order Regression Forest Fields: An Application to 3D Indoor Scene Labelling. Paper presented at the International Conference on Computer Vision (ICCV) 2015.
  • Polok, L., Lui, V., Ila, V., Drummond, T., & Mahony, R. (2015). The Effect of Different Parameterisations in Incremental Structure from Motion. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015, Canberra, Australia.
  • Rezazadegan, F., Shirazi, S., Milford, M., & Upcroft, B. (2015). Evaluation of object detection proposals under condition variations. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Boston, Mass.
  • Rezazadegan, F., Shirazi, S., Sunderhauf, N., Milford, M., & Upcroft, B. (2015). Enhancing human action recognition with region proposals. Paper presented at the Australasian Conference on Robotics and Automation (ACRA2015), Australian National University, Canberra.
  • Salas, M., Latif, Y., Reid, I. D., & Montiel, J. (2015). Trajectory Alignment and Evaluation in SLAM: Horn’s Method vs Alignment on the Manifold. Paper presented at the Robotics: Science and Systems (RSS) 2015.
  • Sergeant, J., Sünderhauf, N., Milford, M., & Upcroft, B. (2015). Multimodal Deep Autoencoders for Control of a Mobile Robot. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.
  • Sokeh, H. S., Gould, S., & Renz, J. (2015). Determining interacting objects in human-centric activities via qualitative spatio-temporal reasoning. Paper presented at the Asian Conference on Computer Vision (ACCV) 1-5 Nov. 2014, Cham, Switzerland.
  • Spek, A., & Drummond, T. (2015). A Fast Method For Computing Principal Curvatures From Range Images. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.
  • Sünderhauf, N., Dayoub, F., McMahon, S., Eich, M., Upcroft, B., & Milford, M. (2015). SLAM–Quo Vadis? In Support of Object Oriented and Semantic SLAM. Paper presented at the Robotics: Science and Systems (RSS) 2015, Rome, Italy.
  • Sünderhauf, N., Dayoub, F., Shirazi, S., Upcroft, B., & Milford, M. (2015). On the Performance of ConvNet Features for Place Recognition. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.
  • Sünderhauf, N., Upcroft, B., & Milford, M. (2015). Continuous Factor Graphs For Holistic Scene Understanding. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  • Wang, P., Shen, C., & van den Hengel, A. (2015). Efficient SDP inference for fully-connected CRFs based on low-rank decomposition. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Piscataway, NJ, USA.
  • Wang, X., Sekercioglu, Y. A., & Drummond, T. (2015). Self-calibration in visual sensor networks equipped with RGB-D cameras. Paper presented at the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015, South Brisbane, QLD.
  • Weberruss, J., Kleeman, L., & Drummond, T. (2015). ORB Feature Extraction and Matching in Hardware. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.
  • Zhang, F., Leitner, J., Milford, M., Upcroft, B., & Corke, P. (2015). Towards Vision-Based Deep Reinforcement Learning for Robotic Motion Control. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.

Journal Articles

  • Aftab, K., Hartley, R., & Trumpf, J. (2015). Generalized Weiszfeld Algorithms for Lq Optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(4), 728-745.
  • Andersh, J., Cherian, A., Mettler, B., & Papanikolopoulos, N. (2015). A vision based ensemble approach to velocity estimation for miniature rotorcraft. Autonomous Robots, 39(2), 123-138.
  • Chen, Z., Lowry, S., Jacobson, A., Hasselmo, M. E., & Milford, M. (2015). Bio-inspired homogeneous multi-scale place recognition. Neural Networks, 72, 48-61.
  • Cherian, A., Morellas, V., & Papanikolopoulos, N. (2015). Bayesian Nonparametric Clustering for Positive Definite Matrices. IEEE Transactions on Pattern Analysis and Machine Intelligence.
  • Dansereau, D. G., Pizarro, O., & Williams, S. B. (2015). Linear Volumetric Focus for Light Field Cameras. ACM Transactions on Graphics (TOG), 34(2), 15.
  • Edussooriya, C. U. S., Dansereau, D. G., Bruton, L. T., & Agathoklis, P. (2015). Five-Dimensional Depth-Velocity Filtering for Enhancing Moving Objects in Light Field Videos. IEEE Transactions on Signal Processing, 63(8), 2151-2163.
  • Fernando, B., Tommasi, T., & Tuytelaars, T. (2015). Joint cross-domain classification and subspace learning for unsupervised adaptation. Pattern Recognition Letters, 65, 60-66.
  • Hui, L., Chunhua, S., van den Hengel, A., & Qinfeng, S. (2015). Worst case linear discriminant analysis as scalable semidefinite feasibility problems. IEEE Transactions on Image Processing, 24(8), 2382-2392.
  • Jacobson, A., Zetao, C., & Milford, M. (2015). Autonomous Multisensor Calibration and Closed-loop Fusion for SLAM. Journal of Field Robotics, 32(1), 85-122.
  • Jingxin, X., Denman, S., Sridharan, S., & Fookes, C. (2015). An Efficient and Robust System for Multiperson Event Detection in Real-World Indoor Surveillance Scenes. IEEE Transactions on Circuits and Systems for Video Technology, 25(6), 1063-1076.
  • Li, X., Shen, C., Dick, A., Zhang, Z., & Zhuang, Y. (2015). Online Metric-Weighted Linear Representations for Robust Visual Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(5), 931-950.
  • Liu, F., Lin, G., & Shen, C. (2015). CRF learning with CNN features for image segmentation. Pattern Recognition, 48(10), 2983-2992.
  • Lowry, S., Sunderhauf, N., Newman, P., Leonard, J. J., Cox, D., Corke, P., & Milford, M. J. (2015). Visual Place Recognition: A Survey. IEEE Transactions on Robotics, 32(1), 1-19.
  • Miaomiao, L., Hartley, R., & Salzmann, M. (2015). Mirror Surface Reconstruction from a Single Image. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(4), 76-73.
  • Neubert, P., Sünderhauf, N., & Protzel, P. (2015). Superpixel-based appearance change prediction for long-term navigation across seasons. Robotics and Autonomous Systems, 69, 15-27.
  • Ryan, D., Denman, S., Sridharan, S., & Fookes, C. (2015). An evaluation of crowd counting methods, features and regression models. Computer Vision and Image Understanding, 130, 1-17.
  • Sa, I., Hrabar, S., & Corke, P. (2015). Outdoor flight testing of a pole inspection UAV incorporating high-speed vision. Field and Service Robotics, 105, 107-121.
  • Shi, Q., Reid, M., Caetano, T., Van den Hengel, A., & Wang, Z. (2015). A hybrid loss for multiclass and structured prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(1), 2-12.
  • Wang, X., Şekercioğlu, Y. A., & Drummond, T. (2015). Vision-Based Cooperative Pose Estimation for Localization in Multi-Robot Systems Equipped with RGB-D Cameras. Robotics, 4(1), 1-22.
  • Wang, X., Sekercioglu, Y. A., Drummond, T., Natalizio, E., Fantoni, I., & Fremont, V. (2015). Fast Depth Video Compression for Mobile RGB-D Sensors. IEEE Transactions on Circuits and Systems for Video Technology, 26(4), 673-686.
  • Warren, M., Mejias, L., Kok, J., Yang, X., Gonzalez, L. F., & Upcroft, B. (2015). An automated emergency landing system for fixed-wing aircraft: Planning and control. Journal of Field Robotics.
  • Zetao, C., Yuen, J., Crawford, R., Jiang, C., Chengtie, W., & Yin, X. (2015). The effect of osteoimmunomodulation on the osteogenic effects of cobalt incorporated -tricalcium phosphate. Biomaterials, 61, 126-138.

2014

  • Anantharajah, K., Ge, Z., McCool, C., Denman, S., Fookes, C., Corke, P., Tjondronegoro, D., & Sridharan, S. “Local inter-session variability modelling for object classification.”, IEEE Winter Conference on Applications of Computer Vision (WACV), 2014.
  • Anh Ngo, T. & Carneiro, G.  “Fully Automated Non-rigid Segmentation with Distance Regularized Level Set Evolution Initialized and Cosntrained by Deep-structured Inference.” CVPR 2014.
  • Chen, Q., & Carneiro, G.  “Artistic Image Analysis using the Composition of Human Figures.”  ECCV 2014 Workshop. Springer ISBN 978-3-319-16177-8
  • Chen, Z., Lam, O., Jacobson, A., & Milford, M., “Convolutional Neural Network-based Place Recognition”, 2014 Australasian Conference on Robotics and Automation
  • Chen, Z.; Jacobson, A., Erdem, U. M., Hasselmo, M. E., Milford, M. “Multi-scale bio-inspired place recognition”, in Robotics and Automation (ICRA), 2014 IEEE International Conference on, pp.1895-1901, 2014.
  • Chi, Y., & Porikli, F,. Classification and boosting with multiple collaborative representations, IEEE Transaction on Pattern Recognition and Machine Intelligence (PAMI), August 2014
  • Eriksson, A., & Isaksson, M. Pseudoconvex Proximal Splitting. Conference on Computer Vision and Pattern Recognition. CVPR, Columbus, USA, 2014.
  • Eriksson, A., Isaksson, M., & Chin, T-J. High-Breakdown Bundle Adjustment, IEEE Winter Conference on Applications of Computer Vision WACV 2015.
  • Faraki, M., Harandi, M., & Porikli, F. Material classification on symmetric positive definite manifolds, IEEE Winter Applications and Computer Vision Conference (WACV), 2015
  • Harandi, H., Salzmann, M., & Porikli, F. Bregman divergences for infinite dimensional covariance matrices, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014
  • Harandi, M. T., Salzmann, M., & Hartley, R. “From manifold to manifold: geometry-aware dimensionality reduction for SPD matrices”, in Computer Vision–ECCV 2014, pp17-32, 2014.
  • Isaksson, M., & Eriksson, A. Analysis of the Inverse Kinematics Problem for 3-DOF Axis-Symmetric Parallel Manipulators with Parasitic Motion IEEE International Conference on Robotics and Automation ICRA, Hong Kong, 2014.
  • Jayasumana, S., Hartley, R., Salzmann, M., Li, H., Harandi, M. “Optimizing over radial kernels on compact manifolds”, in 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June, 2014.
  • Ji, P., Li, H., Salzmann, M., & Dai, Y. “Robust Motion Segmentation with Unknown Correspondences.” ECCV (6) 2014: 204-219
  • Ji, P., Salzmann, M., & Li, H. “Efficient dense subspace clustering.” WACV 2014: 461-468
  • Ji, P., Zhong, Y., Li, H., & Salzmann, M. “Null space clustering with applications to motion segmentation and face clustering”, IEEE International Conference on Image Processing 2014 (ICP 2014), Paris, France.
  • Kneip, L., & Li, H. “Efficient Computation of Relative Pose for Multi-camera Systems.” CVPR 2014: 446-453
  • Kneip, L., Li, H., & Seo, Y. “UPnP: An Optimal O(n) Solution to the Absolute Pose Problem with Universal Applicability.” ECCV (1) 2014: 127-142
  • Lam, O., Dayoub, F., Schulz, R., & Corke, P. “Text recognition approaches for indoor robotics : a compari” in Australasian Conference on Robotics & Automation (ACRA2014), (University of Melbourne, Melbo VIC), December 2014.
  • Li, H., Li, Y., & Porikli, F. DeepTrack: learning discriminative feature representations by convolutional neural networks for visual tracking, (multiple CNNs), British Machine Vision Conference (BMVC), 2014
  • Li, H., Li, Y., & Porikli, F. Robust online visual tracking with an single convolutional neural network, Asian Conference on Computer Vision (ACCV), 2014
  • Lin, G., Shen, C., & Wu, J. “Optimizing ranking measures for compact binary code learning”. European Conference on Computer Vision (ECCV’14). 2014.
  • Lin, G., Shen, C., Shi, Q., van den Hengel, A., & Suter, D. “Fast supervised hashing with decision trees for high-dimensional data”. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’14). 2014.
  • Liu, L., Shen, C., Wang, L., van den Hengel, A., Wang, C. “Encoding high dimensional local features by sparse coding based Fisher vectors.” Advances in Neural Information Processing Systems (NIPS’14). 2014.
  • Milan, A., Gade, R., Dick, A., Moeslund, T. B., & Ried, I.. Improving Global Multi-target Tracking with Local Updates. Workshop on Visual Surveillance Re-Identification, held at European Conf. Computer Vision, 2014
  • Milford, M., Firn, J., Beattie, J, Jacobson, A., Pepperell, E., Mason, E., Kimlin, M., & Dunbabin, M. “Automated Sensory Data Alignment for Environmental and Epidermal Change Monitoring”, 2014 Australasian Conference on Robotics and Automation
  • Nascimento, J. & Carneiro, G. “Non-rigid Segmentation using Sparse Low dimensional Manifolds and Deep Belief Networks”. CVPR 2014.
  • Nasihatkon, B., Hartley, R., & Trumpf, J. “On Projective Reconstruction In Arbitrary Dimensions”, in Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, pp477-484, 2014.
  • Ni, J., Marks, T. K., Tuzel, O., & Porikli, F. Detecting 3D geometric boundaries of indoor scenes under varying lighting, IEEE Winter Applications and Computer Vision Conference (WACV), 2014
  • O’Sullivan, L. & Corke, P. “Empirical modelling of rolling shutter effect,” in Proc. IEEE Int. Conf. Rob and Automation, (Hong Kong), pp. 5277–5283, 2014.
  • Olsson, C., Ulen, J., & Eriksson, A. Local Refinement for Stereo Regularization International Conference on Pattern Recognition ICPR, Stockholm, 2014
  • Paisitkriangkrai, S., Shen, C., & van den Hengel, A. “Strengthening the effectiveness of pedestrian detection with spatially pooled features.” European Conference on Computer Vision (ECCV’14). 2014.
  • Sa, I., Hrabar, S., & Corke, P. “Inspection of pole-like structures using a vision-controlled vtol uav and sh autonomy,” in Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference pp. 4819–4826, Sept 2014.
  • Sharazi, S. Object Tracking via non-Euclidean geometry: A Grassmann approach, IEEE Winter Conference on Applications of Computer Vision (WACV) 2014
  • Shi, Q., Reid, M., Caetano, T., van den Hengel, A., & Wang, Z.  “A Hybrid Loss for Multiclass and Structured Prediction”, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 37(1): 2-12, 2015. ERA [A*]
  • Shu, X., Porikli, F,. & Ahuja, N. Robust orthonormal subspace learning: efficient recovery of corrupted low-rank matrices, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014
  • Singh, A., Porikli, F., & Ahuja, N. Super-resolving noisy images, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014
  • Soni, J. H., & Porikli, F. Recycled linear classifiers for multiclass classification, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2014
  • Tao, L., Porikli, F., & Vidal R. Sparse dictionaries for semantic segmentation, European Conference on Computer Vision (ECCV), 2014
  • Topkaya, S., Erdogan, H., & Porikli, F. Counting people by clustering person detector outputs, IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), 2014 (Best Poster Award)
  • Wang,  Y., Jodoin, P. M., Porikli, F., Konrad, J., Benezeth, Y., & Ishwar,  P. CDnet 2014: an expanded change detection benchmark dataset , IEEE Change Detection Workshop (CDNet) in conjunction with CVPR, 2014
  • Zhu, G, Porikli, F,. Ming, Y, & Li, H. Lie-Struck: affine tracking on Lie groups using structured SVM, IEEE Winter Applications and Computer Vision Conference (WACV), 2015


Name Location Role
Zongyuan GeQUTPhD Candidate
Zhibin LiaoUniversity of AdelaidePhD Candidate
Zetao “Jason” ChenQUTPhD Candidate
Yuchao JiangUniversity of AdelaidePhD Candidate
Yi “Joey” ZhouANUPhD Candidate
Yasir LatifUniversity of AdelaideResearch Fellow
Yan ZouMonashPhD Candidate
Xiaoqin WangMonashPhD Candidate
Will ChamberlainQUTPhD Candidate
Viorela IlaANUResearch Fellow
Vincent LuiMonashPhD Candidate
Vijay KumarUniversity of AdelaideResearch Fellow
Trung Than PhamUniversity of AdelaideResearch Fellow
Tristan PerezQUTAssociate Investigator
Tracy KellyQUTFinance & Administration Officer
Tong ShenUniversity of AdelaidePhD Candidate
Tom DrummondMonash UniversityChief Investigator
Tim MacugaQUTCommunications and Media Officer
Thuy MaiUniversity of AdelaideNode Administration Officer
Thanuja DharmasiriMonashPhD Candidate
Tat-Jun ChinUniversity of AdelaideAssociate Investigator
Sue KeayQUTChief Operating Officer
Stephen GouldANUChief Investigator
Sourav GargQUTPhD Candidate
Sean McMahonQUTPhD Candidate
Sareh ShiraziQUTResearch Fellow
Sarah AllenQUTNode Administration Officer, PA to Centre Director Professor Peter Corke
Ruth SchulzQUTResearch Fellow
Ross CrawfordQUTAssociate Investigator
Rodrigo Santa CruzANUPhD Candidate
Rob MahonyANUChief Investigator
Richard HartleyANUChief Investigator
Riccardo SpicaANUPhD Candidate
Qinfeng ShiUniversity of AdelaideAssociate Investigator
Philip TorrOxfordPartner Investigator
Peter KujalaQUTPhD Candidates
Peter CorkeQUTCentre Director
Peter AndersonANUPhD Candidate
Paul NewmanOxfordPartner Investigator
Niko SuenderhaufQUTResearch Fellow
Mike BradyOxfordCentre Advisory Committee
Michelle SimmonsUNSWCentre Advisory Committee
Michael MilfordQUTChief Investigator
Matt DunbabinQUTAssociative Investigators
Markus EichQUTResearch Fellow
Marc PollefeysETH ZurichPartner Investigator
Mandyam SrinivasanUniversity of QueenslandCentre Advisory Committee
Luis Mejias AlvarezQUTAssociate Investigator
Lin WuUniversity of AdelaideResearch Fellow
Laurent KneipANUAssociative Investigators
Khurrum AftabMonash UniversityResearch Fellow
Kate AldridgeQUTCentre Administrative Coordinator
Juxi LeitnerQUTResearch Fellow
Juan AdarveANUPhD Candidate
Jonghyuk KimANUAssociate Investigator
Jonathan RobertsQUTChief Investigator
John SkinnerQUTPhD Candidate
Jochen TrumpfANUAssociate Investigator
Jeffrey DevarajQUTPhD Candidate
Jason FordQUTAssociate Investigator
Jae-Hak KimUniversity of AdelaideResearch Fellow
Inkyu SaQUTResearch Fellow
Ian ReidUniversity of AdelaideDeputy Director
Hui LiUniversity of AdelaidePhD Candidate
Hugh Durrant-WhyteUniversity of SydneyCentre Advisory Committee
Hongdong LiANUChief Investigator
Gustavo CarneiroUniversity of AdelaideChief Investigator
Guosheng LinUniversity of AdelaideResearch Fellow
Greg LeeQUTExternal Engagement Coordinator
Gordon WyethQUTChief Investigator
Frank DellaertOxfordPartner Investigator
Francois ChaumetteInriaPartner Investigator
Feras DayoubQUTResearch Fellow
Fatih PorikliANUAssociate Investigator
Fangyi ZhangQUTPhD Candidate
Fahimeh RezazadeganQUTPhD Candidate
Edison GuoANUPhD Candidate
Donald DansereauQUTResearch Fellow
Dinesh GamageMonashResearch Fellow
David SuterUniversity of AdelaideAssociate Investigator
David HallQUTPhD Candidate
David BallQUTResearch Fellow
Dan RichardsQUTPhD Candidates
Clinton FookesQUTAssociate Investigator
Chuong NguyenANUResearch Fellow
Chunhua ShenUniversity of AdelaideChief Investigator
Chris McCoolQUTResearch Fellow
Chris LehnertQUTResearch Fellow
Chris JefferyQUTPhD Candidate
Bohan ZhuangUniversity of AdelaidePhD Candidate
Ben UpcroftQUTChief Investigator
Ben TalbotQUTPhD Candidate
Ben MeyerMonashPhD Candidate
Ben HarwoodMonashPhD Candidate
Basura FernandoANUResearch Fellow
Anton Van Den HengelUniversity of AdelaideChief Investigator
Anthony DickUniversity of AdelaideAssociate Investigator
Anoop CherianANUResearch Fellow
Anjali JaiprakashQUTResearch Fellow
Andrew SpekMonashPhD Candidate
Andrew EnglishQUTPhD Candidate
Andrew DavisonImperial College LondonPartner Investigator
Andres Felipe Marmol VelezQUTPhD Candidate
Anders ErikssonQUTResearch Fellow
Alex ZelinskyDefence Science and Technology OrganisationCentre Advisory Committee
Ajay PandeyQUTResearch Fellow
Ahmet SekerciogluMonash UniversityAssociate Investigator
Adam TowQUTPhD Candidate
Adam JacobsonQUTPhD Candidate