Addressing VAST 2016 mini challenge 2 with POLAR kermode, classifier, excel on a power wall and data timelines

Conference paper


Attfield, S., Hewitt, D., Xu, K., Passmore, P., Wagstaff, A., Phillips, G., Windridge, D., Dash, G., Chapman, R. and Mason, L. 2016. Addressing VAST 2016 mini challenge 2 with POLAR kermode, classifier, excel on a power wall and data timelines. IEEE VAST Challenge 2016. Baltimore, MD, USA 23 Oct 2016
TypeConference paper
TitleAddressing VAST 2016 mini challenge 2 with POLAR kermode, classifier, excel on a power wall and data timelines
AuthorsAttfield, S., Hewitt, D., Xu, K., Passmore, P., Wagstaff, A., Phillips, G., Windridge, D., Dash, G., Chapman, R. and Mason, L.
Abstract

We describe our approach to addressing Mini Challenge 2 of the 2016 IEEE VAST Challenge. We describe four tools: POLAR Kermode, Classifier, Excel with conditional formatting on a power wall and Data Timelines.

LanguageEnglish
ConferenceIEEE VAST Challenge 2016
Publication dates
Print23 Oct 2016
Publication process dates
Deposited20 Jun 2017
Accepted13 Sep 2016
Output statusPublished
Accepted author manuscript
Copyright Statement

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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Brown, M., Windridge, D. and Guillemaut, J. 2015. A generalisable framework for saliency-based line segment detection. Pattern Recognition. 48 (12), pp. 3993-4011. https://doi.org/10.1016/j.patcog.2015.06.015
A novel Markov logic rule induction strategy for characterizing sports video footage
Windridge, D., Kittler, J., De Campos, T., Yan, F., Christmas, W. and Khan, A. 2015. A novel Markov logic rule induction strategy for characterizing sports video footage. IEEE MultiMedia. 22 (2), pp. 24-35. https://doi.org/10.1109/MMUL.2014.36
Artificial co-drivers as a universal enabling technology for future intelligent vehicles and transportation systems
Da Lio, M., Biral, F., Bertolazzi, E., Galvani, M., Bosetti, P., Windridge, D., Saroldi, A. and Tango, F. 2015. Artificial co-drivers as a universal enabling technology for future intelligent vehicles and transportation systems. IEEE Transactions on intelligent transportation systems. 16 (1), pp. 244-263. https://doi.org/10.1109/TITS.2014.2330199
Breast cancer data analytics with missing values: a study on ethnic, age and income groups
Tirunagari, S., Poh, N., Abdulrahman, H., Nemmour, N. and Windridge, D. 2015. Breast cancer data analytics with missing values: a study on ethnic, age and income groups. ArXiv e-prints: Quantitative Biology > Quantitative Methods. https://doi.org/10.48550/arXiv.1503.03680
Multilevel Chinese takeaway process and label-based processes for rule induction in the context of automated sports video annotation
Khan, A., Windridge, D. and Kittler, J. 2014. Multilevel Chinese takeaway process and label-based processes for rule induction in the context of automated sports video annotation. IEEE Transactions on Cybernetics. 44 (10), pp. 1910-1923. https://doi.org/10.1109/TCYB.2014.2299955
Domain anomaly detection in machine perception: a system architecture and taxonomy
Kittler, J., Christmas, W., De Campos, T., Windridge, D., Yan, F., Illingworth, J. and Osman, M. 2014. Domain anomaly detection in machine perception: a system architecture and taxonomy. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36 (5), pp. 845-859. https://doi.org/10.1109/TPAMI.2013.209
A saliency-based framework for 2D-3D registration
Brown, M., Guillemaut, J. and Windridge, D. 2014. A saliency-based framework for 2D-3D registration. 9th International Conference on Computer Vision Theory and Applications (VISAPP 2014). Lisbon, Portugal 05 - 08 Jan 2014 SciTePress. pp. 265-273 https://doi.org/10.5220/0004675402650273
Supervised selective kernel fusion for membrane protein prediction
Tatarchuk, A., Sulimova, V., Torshin, I., Mottl, V. and Windridge, D. 2014. Supervised selective kernel fusion for membrane protein prediction. Comin, M., Käll, L., Marchiori, E., Ngom, A. and Rajapakse, J. (ed.) 9th IAPR International Conference Pattern Recognition in Bioinformatics (PRIB 2014). Stockholm, Sweden 21 - 23 Aug 2014 Springer. pp. 98-109 https://doi.org/10.1007/978-3-319-09192-1_9
Challenges in designing an online healthcare platform for personalised patient analytics
Poh, N., Tirunagari, S. and Windridge, D. 2014. Challenges in designing an online healthcare platform for personalised patient analytics. 2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD). Orlando, FL., USA 09 - 12 Dec 2014 IEEE. pp. 1-6 https://doi.org/10.1109/CIBD.2014.7011526
Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses
Tirunagari, S., Poh, N., Aliabadi, K., Windridge, D. and Cooke, D. 2014. Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Orlando, FL., USA 09 - 12 Dec 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 304-309 https://doi.org/10.1109/CIDM.2014.7008682
Non-enumerative cross validation for the determination of structural parameters in feature-selective SVMs
Chernousova, E., Levdik, P., Tatarchuk, A., Mottl, V. and Windridge, D. 2014. Non-enumerative cross validation for the determination of structural parameters in feature-selective SVMs. 22nd International Conference on Pattern Recognition ICPR 2014. Stockholm, Sweden 24 - 28 Aug 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 3654-3659 https://doi.org/10.1109/ICPR.2014.628
Linear regression via elastic net: non-enumerative leave-one-out verification of feature selection
Chernousova, E., Razin, N., Krasotkina, O., Mottl, V. and Windridge, D. 2014. Linear regression via elastic net: non-enumerative leave-one-out verification of feature selection. in: Aleskerov, F., Goldengorin, B. and Pardalos, P. (ed.) Clusters, Orders, and Trees: Methods and Applications: In Honor of Boris Mirkin's 70th Birthday New York Springer.
Automatic annotation of tennis games: an integration of audio, vision, and learning
Yan, F., Kittler, J., Windridge, D., Christmas, W., Mikolajczyk, K., Cox, S. and Huang, Q. 2014. Automatic annotation of tennis games: an integration of audio, vision, and learning. Image and Vision Computing. 32 (11), pp. 896-903. https://doi.org/10.1016/j.imavis.2014.08.004
High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP)
Abbey, C., Hope, C., Sterr, A., Elangovan, P., Geades, N., Windridge, D., Young, K., Wells, K. and Mello-Thoms, C. 2013. High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP). SPIE Proceedings Vol. 8673. https://doi.org/10.1117/12.2007557
Looking to score: the dissociation of goal influence on eye movement and meta-attentional allocation in a complex dynamic natural scene
Taya, S., Windridge, D. and Osman, M. 2012. Looking to score: the dissociation of goal influence on eye movement and meta-attentional allocation in a complex dynamic natural scene. PLoS ONE. 7 (6). https://doi.org/10.1371/journal.pone.0039060
A user study on curved edges in graph visualization
Xu, K., Rooney, C., Passmore, P., Ham, D. and Nguyen, P. 2012. A user study on curved edges in graph visualization. IEEE Transactions on Visualization and Computer Graphics. 18 (12), pp. 2449 -2456. https://doi.org/10.1109/TVCG.2012.189
Genetic sequences: tracing the mutations of a disease.
Mitchell, I., Passmore, P. and Xu, K. 2010. Genetic sequences: tracing the mutations of a disease. IEEE VAST Symposium 2010 Challenge. Salt Lake City, Utah, USA 24 - 29 Oct 2010
Hospitalization records: characterization of pandemic spread.
Passmore, P., Zheng, Y., Rooney, C., Al-Sheikh, T. and Xu, K. 2010. Hospitalization records: characterization of pandemic spread. IEEE VAST Symposium 2010 Challenge. Salt Lake City, Utah, USA 24 - 29 Oct 2010
Integration of geographic information system and RADARSAT synthetic aperture radar data using a self-organizing map network as compensation for realtime ground data in automatic image classification
Shepherd, I., Passmore, P. and Kamal, M. 2010. Integration of geographic information system and RADARSAT synthetic aperture radar data using a self-organizing map network as compensation for realtime ground data in automatic image classification. Journal of Applied Remote Sensing. 4 (1), pp. 1-13. https://doi.org/10.1117/1.3457166
Statistical analysis for brain EIT images using SPM.
Zhang, Y., Passmore, P., Yerworth, R. and Bayford, R. 2005. Statistical analysis for brain EIT images using SPM. Institute of Electrical and Electronics Engineers. pp. 60-67 https://doi.org/10.1109/MEDIVIS.2005.17
Models of cell assembly decay
Passmore, P. and Huyck, C. 2008. Models of cell assembly decay. Institute of Electrical and Electronics Engineers. pp. 1-6 https://doi.org/10.1109/UKRICIS.2008.4798946
Visualization of multidimensional and multimodal tomographic medical imaging data, a case study
Zhang, Y., Passmore, P. and Bayford, R. 2009. Visualization of multidimensional and multimodal tomographic medical imaging data, a case study. Philosophical Transactions of the Royal Society of London. A: Mathematical and Physical Sciences. 367 (1900), pp. 3121-3148. https://doi.org/10.1098/rsta.2009.0084
Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution
Poh, N., Windridge, D., Mottl, V., Tatarchuk, A. and Eliseyev, A. 2010. Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution. IEEE Transactions on Information Forensics and Security. 5 (3), pp. 461-469. https://doi.org/10.1109/TIFS.2010.2053535
Invariance of visual perception
Chikhman, V., Shelepin, Y., Foreman, N., Passmore, P., Vakhrameeva, O. and Pronin, S. 2008. Invariance of visual perception. Experimental Psychology. 1, pp. 7-33.
Viewpoint invariance in the recognition of 3-D depth-rotated figures
Chikhman, V., Shelepin, Y., Foreman, N. and Passmore, P. 2008. Viewpoint invariance in the recognition of 3-D depth-rotated figures. Perception. 37.
The estimation of quantitative ranges of invariance in visual perception
Chikhman, V., Shelepin, Y., Vakhrameeva, O., Pronin, S., Foreman, N. and Passmore, P. 2009. The estimation of quantitative ranges of invariance in visual perception. Perception. 38.
Task based visualization of 5D brain EIT data
Zhang, Y., Passmore, P. and Bayford, R. 2009. Task based visualization of 5D brain EIT data. SAC09: The 2009 ACM Symposium on Applied Computing. Honolulu Hawaii, USA 08 - 12 Mar 2009 New York Association for Computing Machinery (ACM). pp. 831-835 https://doi.org/10.1145/1529282.1529459
Dynamics in proportionate selection.
Mitchell, I., Agrawal, A., Litovski, I. and Passmore, P. 2005. Dynamics in proportionate selection. in: International Conference on Adaptive and Natural Computnig Alogorithms, Coimbra, Portugal. Proceedings. Vienna. Springer. pp. 226-229
Colour vision model-based approach for segmentation of traffic signs
Gao, X., Hong, K., Passmore, P., Podladchikova, L. and Shaposhnikov, D. 2008. Colour vision model-based approach for segmentation of traffic signs. EURASIP Journal on Image and Video Processing. 2008. https://doi.org/10.1155/2008/386705
Visualization and post-processing of 5D Brain Images
Zhang, Y., Passmore, P. and Bayford, R. 2005. Visualization and post-processing of 5D Brain Images. 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Shanghai, China 01 - 04 Sep 2005 IEEE. pp. 1083-1086 https://doi.org/10.1109/IEMBS.2005.1616607