2024 |
McLeod, S., Chng, C. K., Ono, T., Shimizu, Y., Hemmi, R., Holden, L., . . . Chin, T. J. (2024). Robust Perspective-n-Crater for Crater-based Camera Pose Estimation. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp. 6760-6769). DOI |
2024 |
Faulkner, R., Haub, L., Ratcliffe, S., Reid, I., & Chin, T. J. (2024). Semantic Segmentation on 3D Point Clouds with High Density Variations. In 2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023 (pp. 212-222). Online: IEEE. DOI |
2023 |
Ng, Y., Latif, Y., Chin, T. -J., & Mahony, R. (2023). Asynchronous Kalman Filter for Event-Based Star Tracking. In L. Karlinsky, T. Michaeli, & K. Nishino (Eds.), Proceedings of Computer Vision ECCV Vol. 13801 LNCS (pp. 66-79). Tel Aviv, Israel: Springer Nature Switzerland. DOI Scopus4 |
2023 |
McLeod, S., Meoni, G., Izzo, D., Mergy, A., Liu, D., Latif, Y., . . . Chin, T. -J. (2023). Globally Optimal Event-Based Divergence Estimation for Ventral Landing. In L. Karlinsky, T. Michaeli, & K. Nishino (Eds.), Proceedings, Part I Workshops of the 17th European Conference on Computer Vision (ECCV 2022), as published in Lecture Notes in Computer Science Vol. 13801 (pp. 3-20). Cham, Switzerland: Springer. DOI Scopus3 |
2022 |
Doan, A. D., Sasdelli, M., Suter, D., & Chin, T. J. (2022). A Hybrid Quantum-Classical Algorithm for Robust Fitting. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2022) Vol. 2022-June (pp. 417-427). Online: IEEE. DOI Scopus16 WoS1 |
2022 |
Chen, B., Chin, T. J., & Klimavicius, M. (2022). Occlusion-Robust Object Pose Estimation with Holistic Representation. In Proceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022 Vol. 22 (pp. 2223-2233). Waikoloa, HI, USA: IEEE. DOI Scopus10 WoS1 |
2022 |
Du, A., Chen, B., Chin, T. J., Law, Y. W., Sasdelli, M., Raja Segaran, R., & Campbell, D. (2022). Physical Adversarial Attacks on an Aerial Imagery Object Detector. In Proceedings 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2022) (pp. 3798-3808). Online: IEEE. DOI Scopus30 WoS6 |
2022 |
Sachdeva, R., Hammond, R., Bockman, J., Arthur, A., Smart, B., Craggs, D., . . . Reid, I. (2022). Autonomy and Perception for Space Mining. In 2022 International Conference on Robotics and Automation (ICRA) Vol. abs 1611 3673 (pp. 4087-4093). Philadelphia, PA, USA: IEEE. DOI Scopus3 |
2022 |
Liu, D., Parra, A., Latif, Y., Chen, B., Chin, T. J., & Reid, I. (2022). Asynchronous Optimisation for Event-based Visual Odometry. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 9432-9438). Philadelphia, PA, USA: IEEE. DOI Scopus5 |
2022 |
Chen, B., Bakhshi, A., Batista, G., Ng, B., & Chin, T. J. (2022). Update Compression for Deep Neural Networks on the Edge. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2022-June (pp. 3075-3085). New Orleans, LA, USA: IEEE. DOI Scopus9 WoS3 |
2022 |
Zhang, E., Suter, D., Tennakoon, R., Chin, T. J., Bab-Hadiashar, A., Truong, G., & Gilani, S. Z. (2022). Maximum Consensus by Weighted Influences of Monotone Boolean Functions. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR, 2022) Vol. 2022-June (pp. 8954-8962). Online: IEEE. DOI Scopus1 |
2021 |
Doan, D., Turmukhambetov, D., Latif, Y., Chin, T. J., & Bae, S. (2021). Learning to Predict Repeatability of Interest Points. In Proceedings - IEEE International Conference on Robotics and Automation Vol. 2021-May (pp. 10294-10301). online: IEEE. DOI Scopus3 WoS1 |
2021 |
Chen, B., Liu, D., Chin, T. J., Rutten, M., Derksenv, D., Martens, M., . . . Izzo, D. (2021). Spot the GEO satellites: from dataset to Kelvins SpotGEO Challenge. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2021) (pp. 2086-2094). online: IEEE. DOI Scopus8 WoS1 |
2021 |
Dung, H. A., Chen, B., & Chin, T. J. (2021). A spacecraft dataset for detection, segmentation and parts recognition. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp. 2012-2019). Nashville, TN, USA: IEEE. DOI Scopus40 WoS10 |
2021 |
Liu, D., Parra Bustos, A., & Chin, T. J. (2021). Spatiotemporal Registration for Event-based Visual Odometry. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 4935-4944). online: IEEE. DOI Scopus22 |
2021 |
Parra Bustos, A., Ch'ng, S., Chin, T., Eriksson, A. P., & Reid, I. D. (2021). Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging. In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Vol. abs/2103.08292 (pp. 4296-4305). online: IEEE. DOI Scopus7 |
2021 |
Sasdelli, M., & Chin, T. J. (2021). Quantum Annealing Formulation for Binary Neural Networks. In 2021 Digital Image Computing: Techniques and Applications (DICTA) Vol. 82 (pp. 1-10). online: IEEE. DOI Scopus8 WoS1 |
2021 |
Sasdelli, M., Ajanthan, T., Chin, T. J., & Carneiro, G. (2021). A Chaos Theory Approach to Understand Neural Network Optimization. In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA 2021) Vol. 12 (pp. 1-10). online: IEEE. DOI Scopus1 |
2021 |
Tennakoon, R., Suter, D., Zhang, E., Chin, T. J., & Bab-Hadiashar, A. (2021). Consensus Maximisation Using Influences of Monotone Boolean Functions. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2021) Vol. 52 (pp. 2865-2874). online: IEEE Xplore. DOI Scopus7 WoS2 |
2020 |
Chin, T. J., Suter, D., Ch'ng, S. F., & Quach, J. (2020). Quantum Robust Fitting. In H. Ishikawa, C. -L. Liu, T. Pajdla, & J. Shi (Eds.), 15th Asian Conference on Computer Vision, ACCV 2020 Vol. 12622 (pp. 485-499). Switzerland: Springer. |
2020 |
Chng, C. K., Parra Bustos, A., Chin, T. J., & Latif, Y. (2020). Monocular Rotational Odometry with Incremental Rotation Averaging and Loop Closure.. In Proceedings of the 2020 Digital Image Computing Techniques and Applications (DICTA) (pp. 1-8). online: IEEE. |
2020 |
Bagchi, S., & Chin, T. J. (2020). Event-based star tracking via multiresolution progressive hough transforms. In Proceedings of the 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020 Vol. abs/1906.07866 (pp. 2132-2141). online: IEEE. DOI Scopus16 WoS5 |
2020 |
Ch'ng, S. F., Sogi, N., Purkait, P., Chin, T. J., & Fukui, K. (2020). Resolving marker pose ambiguity by robust rotation averaging with clique constraints. In Proceedings of the International Conference on Robotics and Automation, as published in IEEE Xplore Vol. abs/1909.11888 (pp. 9680-9686). online: IEEE. DOI Scopus11 WoS6 |
2020 |
Liu, D., Parra Bustos, Á., & Chin, T. J. (2020). Globally optimal contrast maximisation for event-based motion estimation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2020) (pp. 6348-6357). online: IEEE. DOI Scopus43 WoS16 |
2020 |
Chen, B., Ting, K. M., & Chin, T. J. (2020). Anomaly detection via neighbourhood contrast. In Proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020), as published in Lecture Notes in Computer Science Vol. 12085 (pp. 647-659). Cham, Switzerland: Springer. DOI |
2020 |
Latif, Y., Doan, A. D., Chin, T. J., & Reid, I. (2020). SPRINT: Subgraph Place Recognition for INtelligent Transportation. In Proceedings of the 2020 IEEE International Conference on Robotics and Automation (pp. 5408-5414). online: IEEE. DOI Scopus3 WoS3 |
2020 |
Purkait, P., Chin, T. J., & Reid, I. (2020). NeuRoRA: Neural Robust Rotation Averaging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12369 LNCS (pp. 137-154). Switzerland: Springer International Publishing. DOI Scopus21 |
2019 |
Ch'ng, S. F., Khosravian Hemami, A., Doan, A., & Chin, T. J. (2019). Outlier-robust manifold pre-integration for INS/GPS fusion. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019) Vol. 33 (pp. 7489-7496). online: IEEE. DOI Scopus11 WoS7 |
2019 |
Doan, D., Latif, Y., Chin, T. J., Liu, Y., Do, T. T., & Reid, I. (2019). Scalable place recognition under appearance change for autonomous driving. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2019-October (pp. 9318-9327). online: IEEE. DOI Scopus49 WoS29 |
2019 |
Cai, Z., Chin, T. J., & Koltun, V. (2019). Consensus maximization tree search revisited. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2019-October (pp. 1637-1645). online: IEEE. DOI Scopus20 |
2019 |
Chen, B., Cao, J., Parra Bustos, A., & Chin, T. (2019). Satellite pose estimation with deep landmark regression and nonlinear pose refinement. In Proceedings: 2019 International Conference on Computer Vision Workshops: ICCV 2019 (pp. 2816-2824). online: IEEE. DOI Scopus121 WoS44 |
2019 |
Le, H., Eriksson, A., Milford, M., Do, T., Chin, T., & Suter, D. (2019). Non-smooth M-estimator for maximum consensus estimation. In British Machine Vision Conference 2018, BMVC 2018 (pp. 1-12). online: BMVA. Scopus1 |
2019 |
Parra Bustos, A., Chin, T. J., Eriksson, A., & Reid, I. (2019). Visual SLAM: Why bundle adjust?. In Proceedings of the 2019 IEEE International Conference on Robotics and Automation Vol. 2019-May (pp. 2385-2391). Montreal, Canada: IEEE. DOI Scopus34 WoS19 |
2019 |
Chin, T. J., Bagchi, S., Eriksson, A., & Van Schaik, A. (2019). Star tracking using an event camera. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2019) Vol. 2019-June (pp. 1646-1655). online: IEEE. DOI Scopus40 WoS13 |
2019 |
Doan, A. -D., Latif, Y., Chin, T., Liu, Y., Ch'ng, S., Do, T. -T., & Reid, I. D. (2019). Visual Localization under Appearance Change: A Filtering Approach.. In Proceedings of 2019 Digital Image Computing Techniques and Applications (DICTA) (pp. 254-261). online: IEEE. DOI Scopus3 |
2018 |
Rubino, C., Del Bue, A., & Chin, T. J. (2018). Practical motion segmentation for urban street view scenes. In Proceedings - IEEE International Conference on Robotics and Automation Vol. 79 (pp. 1879-1886). Online: IEEE. DOI Scopus6 |
2018 |
Eriksson, A., Olsson, C., Kahl, F., & Chin, T. J. (2018). Rotation Averaging and Strong Duality. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 127-135). Online: IEEE. DOI Scopus73 |
2018 |
Zhang, Q., Chin, T. J., & Le, H. M. (2018). A Fast Resection-Intersection Method for the Known Rotation Problem. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 1 (pp. 3012-3021). Online: IEEE. DOI Scopus8 |
2018 |
Chin, T. -J., Cai, Z., & Neumann, F. (2018). Robust fitting in computer vision: easy or hard?. In V. Ferrari, M. Herbert, C. Sminchisescu, & Y. Weiss (Eds.), ECCV: European Conference on Computer Vision Vol. abs/1802.06464 (pp. 715-730). Cham, Switzerland: Springer. DOI Scopus4 WoS19 |
2018 |
Cai, Z., Chin, T., Le, H., & Suter, D. (2018). Deterministic consensus maximization with biconvex programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11216 LNCS (pp. 699-714). Switzerland: Springer Nature. DOI Scopus9 WoS20 |
2018 |
Chin, T. -J., Cai, Z., & Neumann, F. (2018). Robust Fitting in Computer Vision: Easy or Hard?. In CoRR Vol. abs/1802.06464. |
2017 |
Le, H., Chin, T., & Suter, D. (2017). RATSAC - Random tree sampling for maximum consensus estimation. In Y. Guo, H. Li, W. Cai, M. Murshed, Z. Wang, J. Gao, & D. Feng (Eds.), Proceedings DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications Vol. 2017-December (pp. 1-8). Sydney: IEEE. DOI Scopus5 |
2017 |
Le, H., Chin, T. -J., & Suter, D. (2017). An exact penalty method for locally convergent maximum consensus. In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) Vol. 2017-January (pp. 379-387). Online: IEEE. DOI Scopus32 WoS21 |
2017 |
Zhang, Q., Chin, T., & Suter, D. (2017). Quasiconvex Plane Sweep for Triangulation with Outliers. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2017-October (pp. 920-928). Venice, ITALY: IEEE. DOI Scopus4 WoS3 |
2017 |
Marker, R., Chin, T., & Newsam, G. (2017). Efficient geometric matching with polar bounds for aligning star field images. In S. Singh, H. Kurniawati, & P. Pounds (Eds.), Proceedings of the Australasian Conference on Robotics and Automation 2016 Vol. 2016-December (pp. 185-193). Brisbane, QLD: ARAA. |
2017 |
Zhang, Q., & Chin, T. (2017). An efficient meta-algorithm for triangulation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10117 LNCS (pp. 148-161). Switzerland: Springer International Publishing AG. DOI |
2017 |
Khosravian, A., Chin, T., & Reid, I. (2017). A branch-and-bound algorithm for checkerboard extraction in camera-laser calibration. In Proceedings of the 2017 IEEE International Conference on Robotics and Automation Vol. 43 (pp. 6495-6502). Singapore: IEEE. DOI Scopus6 |
2017 |
Khosravian, A., Chin, T., Reid, I., & Mahony, R. (2017). A discrete-time attitude observer on SO(3) for vision and GPS fusion. In Proceedings of the 2017 IEEE International Conference on Robotics and Automation Vol. 0 (pp. 5688-5695). Singapore: IEEE. DOI Scopus9 |
2016 |
Pham, T., Rezatofighi, S., Reid, I., & Chin, T. (2016). Efficient point process inference for large-scale object detection. In Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016) Vol. 2016-December (pp. 2837-2845). Las Vegas, NV: IEEE. DOI Scopus15 WoS11 |
2016 |
Chin, T., Kee, Y., Eriksson, A., & Neumann, F. (2016). Guaranteed outlier removal with mixed integer linear programs. In Proceedings of the 29th IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016 (pp. 5858-5866). Las Vegas, NV: IEEE. DOI Scopus39 WoS29 |
2016 |
Eriksson, A., Bastian, J., Chin, T., & Isaksson, M. (2016). A consensus-based framework for distributed Bundle Adjustment. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 1754-1762). Las Vegas, NV, USA: IEEE. DOI Scopus54 |
2016 |
Le, H., Chin, T., & Suter, D. (2016). Conformal surface alignment with optimal Möbius search. In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops Vol. 2016-December (pp. 2507-2516). Las Vegas, NV: IEEE. DOI Scopus5 WoS4 |
2015 |
Ackermann, H., Scheuermann, B., Chin, T., & Rosenhahn, B. (2015). Randomly walking can get you lost: Graph segmentation with unknown edge weights. In X. -C. Tai, E. Bae, T. Chan, & M. Lysaker (Eds.), Proceedings of the 10th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition Vol. 8932 (pp. 450-463). Hong Kong, China: Springer-Verlag Berlin. DOI |
2015 |
Eriksson, A., Isaksson, M., & Chin, T. (2015). High breakdown bundle adjustment. In Proceedings of the 2015 IEEE Winter Conference on Applications of Computer Vision Vol. 255 (pp. 310-317). Waikoloa, HI: IEEE. DOI Scopus3 WoS3 |
2015 |
Eriksson, A., Pham, T., Chin, T., & Reid, I. (2015). The k-support norm and convex envelopes of cardinality and rank. In Proceedings of the 2015 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 3349-3357). Boston, MA: IEEE. DOI Scopus16 WoS10 |
2015 |
Chin, T., Purkait, P., Eriksson, A., & Suter, D. (2015). Efficient globally optimal consensus maximisation with tree search. In Proceedings of the 2015 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 2413-2421). Boston, MA: IEEE. DOI Scopus53 WoS39 |
2015 |
Liu, W., & Chin, T. (2015). Smooth Globally Warp Locally: Video Stabilization using Homography Fields. In Proceedings of the 2015 International Conference on Digital Image Computing: Techniques and Applications Vol. 30 (pp. 1-8). Adelaide, Australia: IEEE. DOI Scopus7 |
2015 |
Bustos, A., & Chin, T. (2015). Guaranteed outlier removal for rotation search. In Proceedings of the 2015 IEEE International Conference on Computer Vision Vol. 2015 International Conference on Computer Vision, ICCV 2015 (pp. 2165-2173). Santiago, Chile: IEEE. DOI Scopus24 WoS18 |
2014 |
Chin, T., Parra Bustos, A., Brown, M., & Suter, D. (2014). Fast rotation search for real-time interactive point cloud registration. In I3D '14 - Symposium on Interactive 3D Graphics and Games (pp. 55-62). San Francisco, CA, USA: ACM. DOI Scopus8 |
2014 |
Purkait, P., Chin, T., Ackermann, H., & Suter, D. (2014). Clustering with hypergraphs: the case for large hyperedges. In D. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Computer Vision - ECCV 2014, 13th European Conference, Zurich, Switzerland, September 6-12, 2014: Proceedings, Part IV Vol. 8692 LNCS (pp. 672-687). Zurich, Switzerland: Springer International Publishing. DOI Scopus24 WoS19 |
2014 |
Chin, T. J., & Tetlow, M. (2014). Robust attitude estimation to support space monitoring using nano-satellites. In AIAA SPACE 2014 Conference and Exposition. Scopus3 |
2014 |
Bustos, Á., Chin, T., & Suter, D. (2014). Fast rotation search with stereographic projections for 3D registration. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 19 (pp. 3930-3937). Columbus, OH: IEEE. DOI Scopus48 WoS33 |
2013 |
Gao, J., Li, Y., Chin, T., & Brown, M. (2013). Seam-driven image stitching. In Proceedings of Eurographics 2013, the 34th Annual Conference of the European Association for Computer Graphics (pp. 1-4). CD: The Eurographics Association. |
2013 |
Liu, W., Chin, T., Carneiro, G., & Suter, D. (2013). Point correspondence validation under unknown radial distortion. In Proceedings of the IEEE2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013 Vol. 37 (pp. 1-8). USA: IEEE. DOI Scopus2 |
2013 |
Carneiro, G., Liao, Z., & Chin, T. (2013). Closed-loop deep vision. In Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013 Vol. 9 (pp. 1-8). USA: IEEE. DOI |
2013 |
Sathyan, T., Chin, T., Suter, D., & Hedley, M. (2013). Improved wireless tracking using radio frequency and video sensors. In Proceedings of the16th International Conference of Information Fusion, FUSION 2013 (pp. 1442-1449). Online: IEEE. Scopus3 WoS1 |
2013 |
Hernandez Zaragoza, J., Chin, T., Brown, M., & Suter, D. (2013). As-projective-as-possible image stitching with moving DLT. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2339-2346). United States of America: IEEE. DOI Scopus420 WoS253 |
2013 |
Dell'Agnello, D., Carneiro, G., Chin, T., Castellano, G., & Fanelli, A. (2013). Fuzzy clustering based encoding for visual object classification. In Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting, IFSA/NAFIPS 2013 Vol. 2 (pp. 1439-1444). USA: IEEE. DOI Scopus4 WoS2 |
2012 |
Zhou, X., Li, X., Chin, T., & Suter, D. (2012). Superpixel-driven level set tracking. In Proceedings of the IEEE 19th International Conference on Image Processing, ICIP 2012 (pp. 409-412). USA: IEEE. DOI Scopus12 WoS7 |
2012 |
Qin, T., Zhong, B., Chin, T., & Wang, H. (2012). Matting-driven online learning of Hough forests for object tracking. In Proceedings of the IEEE 21st International Conference on Pattern Recognition, ICPR 2012 (pp. 2488-2491). USA: IEEE. Scopus3 |
2012 |
Tran, Q., Chin, T., Carneiro, G., Brown, M., & Suter, D. (2012). In defence of RANSAC for outlier rejection in deformable registration. In Proceedings of the12th European Conference on Computer Vision, ECCV 2012 Vol. 7575 LNCS (pp. 274-287). Germany: Springer-Verlag. DOI Scopus56 WoS44 |
2012 |
Zhou, X., Li, X., Chin, T., & Suter, D. (2012). Adaptive human silhouette reconstruction based on the exploration of temporal information. In Proceedings of the 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 Vol. 36 (pp. 1005-1008). USA: IEEE. DOI Scopus1 WoS1 |
2012 |
Pham, T., Chin, T., Yu, J., & Suter, D. (2012). The random cluster model for robust geometric fitting. In Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012 (pp. 710-717). USA: IEEE. DOI Scopus30 WoS15 |
2011 |
Yu, J., Eriksson, A., Chin, T., & Suter, D. (2011). An adversarial optimization approach to efficient outlier removal. In 2011 IEEE International Conference on Computer Vision (pp. 399-406). 345 E 47TH ST, NEW YORK, NY 10017 USA: IEEE. DOI Scopus19 WoS9 |
2011 |
Wong, H., Chin, T., Yu, J., & Suter, D. (2011). Dynamic and hierarchical multi-structure geometric model fitting. In Proceedings of the 2011 IEEE International Conference on Computer Vision (pp. 1044-1051). USA: IEEE. DOI Scopus126 WoS88 |
2011 |
Pham, T., Chin, T., Yu, J., & Suter, D. (2011). Simultaneous sampling and multi-structure fitting with adaptive reversible jump MCMC. In Proceedings of the 25th Annual Conference on Neural Information Processing Systems (pp. 1-9). Spain: NIPS Foundation. Scopus16 |
2011 |
Yu, J., Chin, T., & Suter, D. (2011). A global optimization approach to robust multi-model fitting. In Proceedings of 2011 IEEE Conferencec on Computer Vision and Pattern Recognition (pp. 2041-2048). 345 E 47TH ST, NEW YORK, NY 10017 USA: IEEE. DOI Scopus57 WoS14 |
2010 |
Li, L., Wang, H., Chin, T., Suter, D., & Zhang, S. (2010). Retrieving 3D CAD models using 2D images with optimized weights. In Proceedings of 2010 3rd International Congress on Image and Signal Processing, CISP 2010 Vol. 4 (pp. 1586-1589). USA: IEEE. DOI Scopus10 |
2010 |
Chin, T., Suter, D., & Wang, H. (2010). Multi-structure model selection via kernel optimisation. In Proceedings of 2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (pp. 3586-3593). 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA: IEEE COMPUTER SOC. DOI Scopus20 WoS13 |
2010 |
Wang, H., Chin, T., & Suter, D. (2010). Visual localization and segmentation based on foreground/background modeling. In Proceedings of 2010 IEEE International Conference on Acoustics, speech and signal processing (pp. 1-4). USA: IEEE. DOI Scopus2 WoS1 |
2010 |
Wong, H., Chin, T., Yu, J., & Suter, D. (2010). Efficient multi-structure robust fitting with incremental top-k lists comparison. In Proceedings of The 10th Asian conference on computer vision (ACCV 2010) Vol. 6495 LNCS (pp. 1-12). www: Springer. DOI Scopus7 WoS1 |
2010 |
Chin, T., Yu, J., & Suter, D. (2010). Accelerated hypothesis generation for multi-structure robust fitting. In Proceedings of ECCV 2010 Vol. 6315 (pp. 533-546). Germany: Springer-Verlag Berlin. DOI Scopus32 WoS28 |
2009 |
Chin, T., & Suter, D. (2009). Keypoint induced distance profiles for visual recognition. In Proceedings of the 2009 Conference on Computer Vision & Recognition (pp. 1239-1246). USA: IEEE. DOI Scopus1 |
2009 |
Chin, T., Wang, H., & Suter, D. (2009). Robust Fitting of Multiple Structures: The Statistical Learning Approach. In Proceedings of The Twelfth IEEE International Conference on Computer Vision (pp. 413-420). USA: IEEE. DOI Scopus96 WoS63 |
2009 |
Chin, T., Wang, H., & Suter, D. (2009). The ordered residual kernel for robust motion subspace clustering. In Proceedings of NIPS 2009 (pp. 333-342). online: NIPS. Scopus33 |
2008 |
Chin, T., You, Y., Coutrix, C., Lim, J., Chevallet, J., & Nigay, L. (2008). Snap2Play: A mixed-reality game based on scene identification. In Advances in Multimedia Modeling. Proceedings of the 14th International Multimedia Modeling Conference, 2008, Kyoto, Japan. Vol. 4903 LNCS (pp. 220-229). Berlin: Springer-Verlag. DOI Scopus4 |
2008 |
Chin, T., Goh, H., & Lim, J. (2008). Using Densely Recorded Scenes for Place Recognition. In Proceedings of the 33rd IEEE International Conference on Acoustics, Speech and Signal Processing, 2008, Las Vegas, Nevada, USA. (pp. 2101-2104). Online: IEEE. DOI Scopus3 |
2008 |
Chin, T., Goh, H., & Lim, J. (2008). Boosting Descriptors Condensed from Video Sequences for Place Recognition. In Proceedings of the CVPR Workshop on Visual Localization for Mobile Platforms (VLMP), 2008, Anchorage, Alaska, USA. (pp. 1-8). Online: IEEE. DOI Scopus6 |
2008 |
You, Y., Chin, T., Lim, J., Chevallet, J., Coutrix, C., & Nigay, L. (2008). Deploying and evaluating a mixed reality mobile treasure hunt: Snap2Play. In MobileHCI 2008: Proceedings of the 10th International Conference on Mobile Human Computer Interaction, 2-5 September, 2008, Amsterdam, The Netherlands. (pp. 5 pages). New York: ACM Press. DOI Scopus10 |
2008 |
Chin, T., Goh, H., & Tan, N. (2008). Exact Integral Images at Generic Angles for 2D Barcode Detection. In Proceedings of the 19th International Conference on Pattern Recognition (ICPR), 2008, Tampa, Florida, USA. Vol. 9 (pp. 1-4). Online: IEEE. DOI Scopus7 |
2007 |
Chin, T., Wang, L., Schindler, K., & Suter, D. (2007). Extrapolating learned manifolds for human activity recognition. In Proceedings of the 14th IEEE International Conference on Image Processing, 2007, San Antonio, Texas, USA. Vol. 1 (pp. 381-384). Online: IEEE. DOI Scopus16 WoS8 |
2006 |
Chin, T., & Suter, D. (2006). A new distance criterion for face recognition using image sets. In P. Narayanan, S. Nayar, & H. Shum (Eds.), Computer Vision - ACCV 2006: 7th Asian Conference on Computer Vision Vol. 3851 LNCS (pp. 549-558). Berlin: Springer-Verlag. DOI Scopus4 WoS2 |
2006 |
Chin, T., Schindler, K., & Suter, D. (2006). Incremental Kernel SVD for Face Recognition with Image Sets. In Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition, 2006, Southampton, U.K. Vol. 2006 (pp. 461-466). Online: IEEE. DOI Scopus55 WoS34 |
2006 |
Faggian, N., Paplinski, A., & Chin, T. (2006). Face Recognition from Video using Active Appearance Model Segmentation. In Proceedings of the 18th International Conference on Pattern Recognition, 2006, Hong Kong. Vol. 1 (pp. 287-290). Online: IEEE. DOI Scopus11 |
2006 |
Chin, T., & Suter, D. (2006). Incremental Kernel PCA for Efficient Non-linear Feature Extraction. In Proceedings of the 17th British Machine Vision Conference, 2006, Edinburgh, U.K. (pp. 939-948). Online: The british Machine Vision Association. Scopus15 |
2006 |
Chin, T., & Suter, D. (2006). Improving the Speed of Kernel PCA on Large Scale Datasets. In Proceedings of the IEEE International Conference on Advanced Video and Signal based Surveillance, 2006, Sydney, NSW, Australia. Vol. 27 (pp. 1-6). Online: IEEE. DOI Scopus6 |
2005 |
Tangkuampien, T., & Chin, T. (2005). Locally Linear Embedding for Markerless Human Motion Capture using Multiple Cameras. In Proceedings of Digital Image Computing: Techniques and Applications, 2005, Cairns, Queensland, Australia. Vol. 290 (pp. 1-8). Online: IEEE. DOI |
2005 |
Chin, T., U, J., Schindler, K., & Suter, D. (2005). Face Recognition from Video by Matching Image Sets. In Proceedings of Digital Image Computing: Techniques and Applications, 2005, Cairns, Queensland, Australia. Vol. 2005 (pp. 1-7). Online: IEEE. DOI Scopus11 |
2005 |
Tangkuampien, T., & Chin, T. J. (2005). Locally linear embedding for markerless human motion capture using multiple cameras. In Proceedings of the Digital Imaging Computing: Techniques and Applications, DICTA 2005 Vol. 2005 (pp. 498-505). IEEE. DOI Scopus8 |