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). Seattle: IEEE. 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 Scopus5 |
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 Scopus20 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 (pp. 2223-2233). Waikoloa, HI, USA: IEEE. DOI Scopus11 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 Scopus34 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) (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 Scopus10 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 Scopus2 |
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 Scopus24 |
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 Scopus8 |
2021 |
Sasdelli, M., & Chin, T. J. (2021). Quantum Annealing Formulation for Binary Neural Networks. In 2021 Digital Image Computing: Techniques and Applications (DICTA) Vol. abs/2107.02751 (pp. 1-10). online: IEEE. DOI Scopus9 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) (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) (pp. 2865-2874). online: IEEE Xplore. DOI Scopus8 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 Scopus45 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 Scopus22 |
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) (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 Scopus51 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 Scopus127 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 Scopus35 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 (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 Scopus75 |
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 (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 (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 Scopus16 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 Scopus40 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 Scopus55 |
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 (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 (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 Scopus25 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 (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 (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 (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 Scopus430 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 (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 Scopus57 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 (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 Scopus127 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 Scopus97 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. (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. (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. (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 |