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2016 Journal Articles [89]

Dictionary Learning for Promoting Structured Sparsity in Hyprspectral Compressive Sensing

*Zhang, L., Wei, W., Zhang, Y., & Shen, C. (2016). Dictionary Learning for Promoting Structured Sparsity in Hyprspectral Compressive Sensing. IEEE Transactions on GeoScience and Remote Sensing, 54(12), pp.7223–7235.

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Unsupervised Feature Learning for Dense Correspondences Across Scenes

Zhang, C., Shen, C., & Shen, T. (2015). Unsupervised Feature Learning for Dense Correspondences Across Scenes. International Journal of Computer Vision, 116(1), pp.90–107.

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Development of a Multi-Channel Concentric Tube Robotic System With Active Vision for Transnasal Nasopharyngeal Carcinoma Procedures

Yu, H., Wu, L., Wu, K., & Ren, H. (2016). Development of a Multi-Channel Concentric Tube Robotic System With Active Vision for Transnasal Nasopharyngeal Carcinoma Procedures. IEEE Robotics and Automation Letters, 1(2), pp.1172–1178.

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Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration

*Yang, J., Li, H., Campbell, D., & Jia, Y. (2016). Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), pp.2241–2254.

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Detecting Rare Events Using Kullback–Leibler Divergence: A Weakly Supervised Approach

Xu, J., Denman, S., Fookes, C., & Sridharan, S. (2016). Detecting rare events using Kullback–Leibler divergence: A weakly supervised approach. Expert Systems with Applications, 54, pp.13–28.

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Hypergraph Modelling for Geometric Model Fitting

Xiao, G., Wang, H., Lai, T., & Suter, D. (2016). Hypergraph modelling for geometric model fitting. Pattern Recognition, 60, pp.748–760.

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Simultaneous Hand–Eye, Tool–Flange, and Robot–Robot Calibration for Comanipulation by Solving the Problem

Wu, L., Wang, J., Qi, L., Wu, K., Ren, H., & Meng, M. Q.-H. (2016). Simultaneous Hand–Eye, Tool–Flange, and Robot–Robot Calibration for Comanipulation by Solving the Problem. IEEE Transactions on Robotics, 32(2), pp.413–428.

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Long-Range Stereo Visual Odometry for Extended Altitude Flight of Unmanned Aerial Vehicles

*Warren, M., Corke, P., & Upcroft, B. (2016). Long-range stereo visual odometry for extended altitude flight of unmanned aerial vehicles. The International Journal of Robotics Research, 35(4), pp.381–403.

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Fast Depth Video Compression for Mobile RGB-D Sensors

*Wang, X., Sekercioglu, Y. A., Drummond, T., Natalizio, E., Fantoni, I., & Fremont, V. (2016). Fast Depth Video Compression for Mobile RGB-D Sensors. IEEE Transactions on Circuits and Systems for Video Technology, 26(4), pp.673–686.

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Correspondence Driven Saliency Transfer

*Wang, W., Shen, J., Shao, L., & Porikli, F. (2016). Correspondence Driven Saliency Transfer. IEEE Transactions on Image Processing, 25(11), pp.5025–5034.

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Efficient Semidefinite Branch-and-Cut for MAP-MRF Inference

*Wang, P., Shen, C., van den Hengel, A., & Torr, P. H. S. (2015). Efficient Semidefinite Branch-and-Cut for MAP-MRF Inference. International Journal of Computer Vision, 117(3), pp.269–289.

View more

Robust Model Fitting Using Higher Than Minimal Subset Sampling

Tennakoon, R. B., Bab-Hadiashar, A., Cao, Z., Hoseinnezhad, R., & Suter, D. (2016). Robust Model Fitting Using Higher Than Minimal Subset Sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2), pp.350–362.

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Teaching Robots Generalizable Hierarchical Tasks Through Natural Language Instruction

Suddrey, G., Lehnert, C., Eich, M., Maire, F., & Roberts, J. (2016). Teaching Robots Generalisable Hierarchical Tasks Through Natural Language Instruction. IEEE Robotics and Automation Letters, 2(1), pp.201–208.

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Unlocking Neural Complexity with a Robotic Key

Stratton, P., Hasselmo, M., & Milford, M. (2016). Unlocking neural complexity with a robotic key. The Journal of Physiology, 594(22), pp.6559–6567.

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A Passivity-Based Approach to Formation Control Using Partial Measurements of Relative Position

Stacey, G., & Mahony, R. (2016). A Passivity-Based Approach to Formation Control Using Partial Measurements of Relative Position. IEEE Transactions on Automatic Control, 61(2), pp.538–543.

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Distributed Formation Control of Networked Mobile Robots in Environments with Obstacles

Seng, W. L., Barca, J. C., Şekercioğlu, Y. A., & Ahmet Ekercio˘ Glu, Y. (2016). Distributed formation control of networked mobile robots in environments with obstacles. Robotica Robotica Robotica, 34(34), pp.1403–1415.

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Strategies for Pre-Emptive Mid-Air Collision Avoidance in Budgerigars

Schiffner, I., Perez, T., Srinivasan, M. V., Angelov, P., Padian, K., Chiappe, L., et.al. (2016). Strategies for Pre-Emptive Mid-Air Collision Avoidance in Budgerigars. PLOS ONE, 11(9), e0162435.

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Deep Learning for Automatic Detection and Classification of Microaneurysms, Hard and Soft Exudates, and Hemorrhages for Diabetic Retinopathy Diagnosis

Saha, S. K., Fernando, B., Xiao, D., Tay-Kearney, M.-L., & Kanagasingam, Y. (2016). Deep Learning for Automatic Detection and Classification of Microaneurysms, Hard and Soft Exudates, and Hemorrhages for Diabetic Retinopathy Diagnosis. Investigative Ophthalmology & Visual Science, 57(12), pp.5962–5962.

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DeepFruits: A Fruit Detection System Using Deep Neural Networks Inkyu Sa *, Zongyuan Ge, Feras Dayoub, Ben Upcroft, Tristan Perez and Chris McCool Science and Engineering Faculty, Queensland University of Technology, Brisbane 4000, Australia * Correspondence: Tel.: +61-449-722-415 Academic Editors: Gabriel Oliver-Codina, Nuno Gracias and Antonio M. López Received: 19 May 2016 / Accepted: 26 July 2016 / Published: 3 August 2016

*Sa, I., Ge, Z., Dayoub, F., Upcroft, B., Perez, T., & McCool, C. (2016). DeepFruits: A Fruit Detection System Using Deep Neural Networks. Sensors, 16(8), pp.1222.

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A Flexible Hierarchical Approach For Facial Age Estimation Based on Multiple Features

Pontes, J. K., Britto, A. S., Fookes, C., & Koerich, A. L. (2016). A flexible hierarchical approach for facial age estimation based on multiple features. Pattern Recognition, 54, pp.34–51.

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Routed Roads: Probabilistic Vision-Based Place Recognition for Changing Conditions, Split Streets and Varied Viewpoints

*Pepperell, E., Corke, P., & Milford, M. (2016). Routed roads: Probabilistic vision-based place recognition for changing conditions, split streets and varied viewpoints. The International Journal of Robotics Research, 35(9), pp.1057–1079.

View more

Fast Rotation Search with Stereographic Projections for 3D Registration

*Parra Bustos, A., Chin, T.-J., Eriksson, A., Li, H., & Suter, D. (2016). Fast Rotation Search with Stereographic Projections for 3D Registration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), pp.2227–2240.

View more

Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning

*Paisitkriangkrai, S., Shen, C., & Hengel, A. van den. (2016). Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(6), pp.1243–1257.

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Contour Completion Without Region Segmentation

*Ming, Y., Li, H., & He, X. (2016). Contour Completion Without Region Segmentation. IEEE Transactions on Image Processing, 25(8), pp.3597–3611.

View more

RatSLAM: Using Models of Rodent Hippocampus for Robot Navigation and Beyond

*Milford, M., Jacobson, A., Chen, Z., & Wyeth, G. (2016). RatSLAM: Using Models of Rodent Hippocampus for Robot Navigation and Beyond. In Robotics Research (pp. 467–485).

View more

Visual Tracking Under Motion Blur

*Ma, B., Huang, L., Shen, J., Shao, L., Yang, M.-H., & Porikli, F. (2016). Visual Tracking Under Motion Blur. IEEE Transactions on Image Processing, 25(12), pp.5867–5876.

View more

Supervised and Unsupervised Linear Learning Techniques for Visual Place Recognition in Changing Environments

*Lowry, S., & Milford, M. J. (2016). Supervised and Unsupervised Linear Learning Techniques for Visual Place Recognition in Changing Environments. IEEE Transactions on Robotics, 32(3), pp.600–613.

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A Generalized Probabilistic Framework for Compact Codebook Creation

*Liu, L., Wang, L., & Shen, C. (2016). A Generalized Probabilistic Framework for Compact Codebook Creation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2), pp.224–37.

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Online Unsupervised Feature Learning for Visual Tracking

*Liu, F., Shen, C., Reid, I., & van den Hengel, A. (2016). Online unsupervised feature learning for visual tracking. Image and Vision Computing, 51(July), pp.84–94.

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Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields

*Liu, F., Shen, C., Lin, G., & Reid, I. (2016). Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(10), pp.2024–2039.

View more

Online Metric-Weighted Linear Representations for Robust Visual Tracking

*Li, X., Shen, C., Dick, A., Zhang, Z. M., & Zhuang, Y. (2016). Online Metric-Weighted Linear Representations for Robust Visual Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(5), pp.931–950.

View more

Convolutional Neural Net Bagging for Online Visual Tracking

*Li, H., Li, Y., & Porikli, F. (2016). Convolutional neural net bagging for online visual tracking. Computer Vision and Image Understanding, 153 (December 2016), pp.120–129.

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A Modular Software Framework for Eye–Hand Coordination in Humanoid Robots

*Leitner, J., Harding, S., Förster, A., & Corke, P. (2016). A Modular Software Framework for Eye–Hand Coordination in Humanoid Robots. Frontiers in Robotics and AI, 3, 26.

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Motion Segmentation Via a Sparsity Constraint

*Lai, T., Wang, H., Yan, Y., Chin, T.-J., & Zhao, W.-L. (2016). Motion Segmentation Via a Sparsity Constraint. IEEE Transactions on Intelligent Transportation Systems, PP (99), 1–11. *Article in press

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A Novel Performance Evaluation Methodology for Single-Target Trackers

*Kristan, M., Matas, J., Leonardis, A., Vojir, T., Pflugfelder, R., Fernandez, G., et.al. (2016). A Novel Performance Evaluation Methodology for Single-Target Trackers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), pp.2137–2155.

View more

State Estimation for Invariant Systems on Lie Groups with Delayed Output Measurements

Khosravian, A., Trumpf, J., Mahony, R., & Hamel, T. (2016). State estimation for invariant systems on Lie groups with delayed output measurements. Automatica, 68, pp.254–265.

View more

Fast Detection of Multiple Objects in Traffic Scenes with a Common Detection Framework

*Hu, Q., Paisitkriangkrai, S., Shen, C., van den Hengel, A., & Porikli, F. (2016). Fast Detection of Multiple Objects in Traffic Scenes With a Common Detection Framework. IEEE Transactions on Intelligent Transportation Systems, 17(4), pp.1002–1014.

View more

Dynamic Kinesthetic Boundary for Haptic Teleoperation of VTOL Aerial Robots in Complex Environments

Hou, X., & Mahony, R. (2016). Dynamic Kinesthetic Boundary for Haptic Teleoperation of VTOL Aerial Robots in Complex Environments. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(5), pp.694–705.

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Automated Fourier Space Region-Recognition Filtering for Off-Axis Digital Holographic Microscopy

*He, X., Nguyen, C. V., Pratap, M., Zheng, Y., Wang, Y., Nisbet, D. R., et.al. (2016). Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy. Biomedical Optics Express, 7(8), pp.3111.

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Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences

Harandi, M. T., Hartley, R., Lovell, B., & Sanderson, C. (2016). Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences. IEEE Transactions on Neural Networks and Learning Systems, 27(6), pp.1294–1306.

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Partitioning de Bruijn Graphs into Fixed-Length Cycles for Robot Identification and Tracking

Grubman, T., Şekercioğlu, Y. A., & Wood, D. R. (2016). Partitioning de Bruijn graphs into fixed-length cycles for robot identification and tracking. Discrete Applied Mathematics, 213, pp.101–113.

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Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling

*Ferrari, R., McKinnon, D., He, H., Smith, R., Corke, P., González-Rivero, M., et.al. (2016). Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling. Remote Sensing, 8(2), pp.113.

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Simple Change Detection from Mobile Light Field Cameras

*Dansereau, D. G., Williams, S. B., & Corke, P. I. (2016). Simple change detection from mobile light field cameras. Computer Vision and Image Understanding, 145(April), pp.160–171.

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Bayesian Nonparametric Clustering for Positive Definite Matrices

Cherian, A., Morellas, V., & Papanikolopoulos, N. (2016). Bayesian Nonparametric Clustering for Positive Definite Matrices. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(5), pp.862–74.

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Measuring the Performance of Single Image Depth Estimation Methods

*Cadena, C., Latif, Y., & Reid, I. D. (2016). Measuring the performance of single image depth estimation methods. In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4150–4157). Daejeon, Korea: IEEE.

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Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age

*Cadena, C., Carlone, L., Carrillo, H., Latif, Y., Scaramuzza, D., Neira, J., et.al. Leonard, J. J. (2016). Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age. IEEE Transactions on Robotics, 32(6), pp.1309–1332.

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Discovering Team Structures in Soccer from Spatiotemporal Data

Bialkowski, A., Lucey, P., Carr, P., Matthews, I., Sridharan, S., & Fookes, C. (2016). Discovering Team Structures in Soccer from Spatiotemporal Data. IEEE Transactions on Knowledge and Data Engineering, 28(10), pp.2596–2605.

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From ImageNet to Mining: Adapting Visual Object Detection with Minimal Supervision

*Bewley, A., & Upcroft, B. (2016). From imagenet to mining: Adapting visual object detection with minimal supervision. In 10th International Conference on Field and Service Robotics, FSR 2015; (Vol. 113, pp. 501–514). Toronto, Canada: Springer Verlag.

View more

Vision-based Obstacle Detection and Navigation for an Agricultural Robot

*Ball, D., Upcroft, B., Wyeth, G., Corke, P., English, A., Ross, P., et.al. (2016). Vision-based Obstacle Detection and Navigation for an Agricultural Robot. Journal of Field Robotics, 33(8), pp.1107–1130.

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A Filter Formulation for Computing Real Time Optical Flow

*Adarve, J. D., & Mahony, R. (2016). A Filter Formulation for Computing Real Time Optical Flow. IEEE Robotics and Automation Letters, 1(2), pp.1192–1199.

View more

Dictionary Learning for Promoting Structured Sparsity in Hyprspectral Compressive Sensing

*Zhang, L., Wei, W., Zhang, Y., & Shen, C. (2016). Dictionary Learning for Promoting Structured Sparsity in Hyprspectral Compressive Sensing. IEEE Transactions on GeoScience and Remote Sensing, 54(12), pp.7223–7235.

View more

Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration

*Yang, J., Li, H., Campbell, D., & Jia, Y. (2016). Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), pp.2241–2254.

View more

Detecting rare events using Kullback–Leibler divergence: A weakly supervised approach

Xu, J., Denman, S., Fookes, C., & Sridharan, S. (2016). Detecting rare events using Kullback–Leibler divergence: A weakly supervised approach. Expert Systems with Applications, 54, pp.13–28.

View more

Hypergraph modelling for geometric model fitting

Xiao, G., Wang, H., Lai, T., & Suter, D. (2016). Hypergraph modelling for geometric model fitting. Pattern Recognition, 60, pp.748–760.

View more

Long-range stereo visual odometry for extended altitude flight of unmanned aerial vehicles

*Warren, M., Corke, P., & Upcroft, B. (2016). Long-range stereo visual odometry for extended altitude flight of unmanned aerial vehicles. The International Journal of Robotics Research, 35(4), pp.381–403.

View more

Fast Depth Video Compression for Mobile RGB-D Sensors

*Wang, X., Sekercioglu, Y. A., Drummond, T., Natalizio, E., Fantoni, I., & Fremont, V. (2016). Fast Depth Video Compression for Mobile RGB-D Sensors. IEEE Transactions on Circuits and Systems for Video Technology, 26(4), pp.673–686.

View more

Correspondence Driven Saliency Transfer

*Wang, W., Shen, J., Shao, L., & Porikli, F. (2016). Correspondence Driven Saliency Transfer. IEEE Transactions on Image Processing, 25(11), pp.5025–5034.

View more

Efficient Semidefinite Branch-and-Cut for MAP-MRF Inference

*Wang, P., Shen, C., van den Hengel, A., & Torr, P. H. S. (2015). Efficient Semidefinite Branch-and-Cut for MAP-MRF Inference. International Journal of Computer Vision, 117(3), pp.269–289.

View more

Robust Model Fitting Using Higher Than Minimal Subset Sampling

Tennakoon, R. B., Bab-Hadiashar, A., Cao, Z., Hoseinnezhad, R., & Suter, D. (2016). Robust Model Fitting Using Higher Than Minimal Subset Sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2), pp.350–362.

View more

Teaching Robots Generalisable Hierarchical Tasks Through Natural Language Instruction

Suddrey, G., Lehnert, C., Eich, M., Maire, F., & Roberts, J. (2016). Teaching Robots Generalisable Hierarchical Tasks Through Natural Language Instruction. IEEE Robotics and Automation Letters, 2(1), pp.201–208.

View more

Unlocking neural complexity with a robotic key

Stratton, P., Hasselmo, M., & Milford, M. (2016). Unlocking neural complexity with a robotic key. The Journal of Physiology, 594(22), pp.6559–6567.

View more

A Passivity-Based Approach to Formation Control Using Partial Measurements of Relative Position

Stacey, G., & Mahony, R. (2016). A Passivity-Based Approach to Formation Control Using Partial Measurements of Relative Position. IEEE Transactions on Automatic Control, 61(2), pp.538–543.

View more

Distributed formation control of networked mobile robots in environments with obstacles

Seng, W. L., Barca, J. C., Şekercioğlu, Y. A., & Ahmet Ekercio˘ Glu, Y. (2016). Distributed formation control of networked mobile robots in environments with obstacles. Robotica Robotica Robotica, 34(34), pp.1403–1415.

View more

Strategies for Pre-Emptive Mid-Air Collision Avoidance in Budgerigars

Schiffner, I., Perez, T., Srinivasan, M. V., Angelov, P., Padian, K., Chiappe, L., et.al. (2016). Strategies for Pre-Emptive Mid-Air Collision Avoidance in Budgerigars. PLOS ONE, 11(9), e0162435.

View more

Deep Learning for Automatic Detection and Classification of Microaneurysms, Hard and Soft Exudates, and Hemorrhages for Diabetic Retinopathy Diagnosis

Saha, S. K., Fernando, B., Xiao, D., Tay-Kearney, M.-L., & Kanagasingam, Y. (2016). Deep Learning for Automatic Detection and Classification of Microaneurysms, Hard and Soft Exudates, and Hemorrhages for Diabetic Retinopathy Diagnosis. Investigative Ophthalmology & Visual Science, 57(12), pp.5962–5962.

View more

DeepFruits: A Fruit Detection System Using Deep Neural Networks

*Sa, I., Ge, Z., Dayoub, F., Upcroft, B., Perez, T., & McCool, C. (2016). DeepFruits: A Fruit Detection System Using Deep Neural Networks. Sensors, 16(8), pp.1222.

View more

A flexible hierarchical approach for facial age estimation based on multiple features

Pontes, J. K., Britto, A. S., Fookes, C., & Koerich, A. L. (2016). A flexible hierarchical approach for facial age estimation based on multiple features. Pattern Recognition, 54, pp.34–51.

View more

Routed roads: Probabilistic vision-based place recognition for changing conditions, split streets and varied viewpoints

*Pepperell, E., Corke, P., & Milford, M. (2016). Routed roads: Probabilistic vision-based place recognition for changing conditions, split streets and varied viewpoints. The International Journal of Robotics Research, 35(9), pp.1057–1079.

View more

Fast Rotation Search with Stereographic Projections for 3D Registration

*Parra Bustos, A., Chin, T.-J., Eriksson, A., Li, H., & Suter, D. (2016). Fast Rotation Search with Stereographic Projections for 3D Registration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), pp.2227–2240.

View more

Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning

*Paisitkriangkrai, S., Shen, C., & Hengel, A. van den. (2016). Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(6), pp.1243–1257.

View more

Contour Completion Without Region Segmentation

*Ming, Y., Li, H., & He, X. (2016). Contour Completion Without Region Segmentation. IEEE Transactions on Image Processing, 25(8), pp.3597–3611.

View more

RatSLAM: Using Models of Rodent Hippocampus for Robot Navigation and Beyond

*Milford, M., Jacobson, A., Chen, Z., & Wyeth, G. (2016). RatSLAM: Using Models of Rodent Hippocampus for Robot Navigation and Beyond. In Robotics Research (pp. 467–485).

View more

Visual Tracking Under Motion Blur

*Ma, B., Huang, L., Shen, J., Shao, L., Yang, M.-H., & Porikli, F. (2016). Visual Tracking Under Motion Blur. IEEE Transactions on Image Processing, 25(12), pp.5867–5876.

View more

Supervised and Unsupervised Linear Learning Techniques for Visual Place Recognition in Changing Environments

*Lowry, S., & Milford, M. J. (2016). Supervised and Unsupervised Linear Learning Techniques for Visual Place Recognition in Changing Environments. IEEE Transactions on Robotics, 32(3), pp.600–613.

View more

Online unsupervised feature learning for visual tracking

*Liu, F., Shen, C., Reid, I., & van den Hengel, A. (2016). Online unsupervised feature learning for visual tracking. Image and Vision Computing, 51(July), pp.84–94.

View more

Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields

*Liu, F., Shen, C., Lin, G., & Reid, I. (2016). Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(10), pp.2024–2039.

View more

Online Metric-Weighted Linear Representations for Robust Visual Tracking

*Li, X., Shen, C., Dick, A., Zhang, Z. M., & Zhuang, Y. (2016). Online Metric-Weighted Linear Representations for Robust Visual Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(5), pp.931–950.

View more

Convolutional neural net bagging for online visual tracking

*Li, H., Li, Y., & Porikli, F. (2016). Convolutional neural net bagging for online visual tracking. Computer Vision and Image Understanding, 153 (December 2016), pp.120–129.

View more

A Modular Software Framework for Eye–Hand Coordination in Humanoid Robots

*Leitner, J., Harding, S., Förster, A., & Corke, P. (2016). A Modular Software Framework for Eye–Hand Coordination in Humanoid Robots. Frontiers in Robotics and AI, 3, 26.

View more

Motion Segmentation Via a Sparsity Constraint

*Lai, T., Wang, H., Yan, Y., Chin, T.-J., & Zhao, W.-L. (2016). Motion Segmentation Via a Sparsity Constraint. IEEE Transactions on Intelligent Transportation Systems, PP (99), 1–11. *Article in press

View more

A Novel Performance Evaluation Methodology for Single-Target Trackers

*Kristan, M., Matas, J., Leonardis, A., Vojir, T., Pflugfelder, R., Fernandez, G., et.al. (2016). A Novel Performance Evaluation Methodology for Single-Target Trackers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), pp.2137–2155.

View more

State estimation for invariant systems on Lie groups with delayed output measurements

Khosravian, A., Trumpf, J., Mahony, R., & Hamel, T. (2016). State estimation for invariant systems on Lie groups with delayed output measurements. Automatica, 68, pp.254–265.

View more

Fast Detection of Multiple Objects in Traffic Scenes With a Common Detection Framework

*Hu, Q., Paisitkriangkrai, S., Shen, C., van den Hengel, A., & Porikli, F. (2016). Fast Detection of Multiple Objects in Traffic Scenes With a Common Detection Framework. IEEE Transactions on Intelligent Transportation Systems, 17(4), pp.1002–1014.

View more

Dynamic Kinesthetic Boundary for Haptic Teleoperation of VTOL Aerial Robots in Complex Environments

Hou, X., & Mahony, R. (2016). Dynamic Kinesthetic Boundary for Haptic Teleoperation of VTOL Aerial Robots in Complex Environments. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(5), pp.694–705.

View more

Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences

*Harandi, M. T., Hartley, R., Lovell, B., & Sanderson, C. (2016). Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences. IEEE Transactions on Neural Networks and Learning Systems, 27(6), pp.1294–1306.

View more

Discovering Team Structures in Soccer from Spatiotemporal Data

Bialkowski, A., Lucey, P., Carr, P., Matthews, I., Sridharan, S., & Fookes, C. (2016). Discovering Team Structures in Soccer from Spatiotemporal Data. IEEE Transactions on Knowledge and Data Engineering, 28(10), pp.2596–2605.

View more

From imagenet to mining: Adapting visual object detection with minimal supervision

*Bewley, A., & Upcroft, B. (2016). From imagenet to mining: Adapting visual object detection with minimal supervision. In 10th International Conference on Field and Service Robotics, FSR 2015; (Vol. 113, pp. 501–514). Toronto, Canada: Springer Verlag.

View more

Vision-based Obstacle Detection and Navigation for an Agricultural Robot

*Ball, D., Upcroft, B., Wyeth, G., Corke, P., English, A., Ross, P., et.al. (2016). Vision-based Obstacle Detection and Navigation for an Agricultural Robot. Journal of Field Robotics, 33(8), pp.1107–1130.

View more

A Filter Formulation for Computing Real Time Optical Flow

*Adarve, J. D., & Mahony, R. (2016). A Filter Formulation for Computing Real Time Optical Flow. IEEE Robotics and Automation Letters, 1(2), pp.1192–1199.

View more

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