Publications

  1. Kar, A., Rai, N., Sikka, K., Sharma, G. (2016). AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos. (submitted) [arXiv preprint]
  2. Sikka, K., Sharma, G. (2016). Discriminatively Trained Latent Ordinal Model for Video Classification. (submitted) [arXiv preprint] [project page]
  3. Sikka, K., Sharma, G., Bartlett, M. (2016). LOMo: Latent Ordinal Model for Facial Analysis in Videos. Computer Vision and Pattern Recognition (CVPR). (Spotlight Presentation) [arXiv preprint] [Supp. video] [project page]
  4. Malmir, M., Sikka, K., Forster, D., Fasel, I., Movellan, J., Cottrell, W, Garrison. (2016). Deep Active Object Recognition by Joint Label and Action Prediction. Computer Vision and Image Understanding (CVIU). (under review) [PDF]
  5. Malmir, M., Sikka, K., Forster D., Movellan, J., Cottrell, W, Garrison. (2015). Deep Q-learning for Active Recognition of GERMS: Baseline performance on a standardized dataset for active learning. British Machine Vision Conference (BMVC). (Acceptance Rate: 33%) [PDF] [short_abstract]
  6. Sikka, K., Giri, R., Bartlett, M. (2015). Joint Clustering and Classification for Multiple Instance Learning. British Machine Vision Conference (BMVC). (Acceptance Rate: 33%) [Project Page/code] [PDF] [short_abstract]
  7. Sikka, K., Dhall, A., Bartlett, M. (2015). Exemplar Hidden Markov Models for Classification of Facial Expressions in Videos. IEEE Conference on Computer Vision and Pattern Recognition Workshops ( CVPRW). [Project Page/code] [PDF] [Presentation]
  8. Sikka, K., Ahmed, A., Diaz, D., Goodwin, M., Craig, K., Bartlett, M., Huang, J. (2015). Automated Assessment of Children's Post-Operative Pain Using Computer Vision. Pediatrics. (Impact Factor: 5.47) [PDF] [Suppl.]
  9. Dhall, A., Joshi, J., Sikka, K., Goecke, K. and Sebe, N. (2015). The More the Merrier: Analysing the Affect of a Group of People In Images. IEEE International Conference on Automatic Face and Gesture Recognition ( FG). (Oral Presentation) [PDF]
  10. Sikka, K. (2014). Facial Expression Analysis for Estimating Pain in Clinical Settings. Proceedings of the 16th International Conference on Multimodal Interaction (ICMI), Doctoral Consortium. [PDF]
  11. Dhall, A., Goecke, R., Joshi, J., Sikka, K. and Gedeon, T. (2014). Emotion recognition in the wild challenge 2014: Baseline, data and protocol. Proceedings of the 16th International Conference on Multimodal Interaction ( ICMI). ( EmotiW'14 Challenge) [PDF]
  12. Sikka, K., Dhall, A. and Bartlett, M. (2014). Weakly Supervised Pain Localization and Classification with Multiple Segment Learning. The Best of Face and Gesture 2013, Image and Vision Computing (Elsevier). (Impact Factor: 1.959) [PDF]
  13. Dhall, A., Sikka, K., Littlewort, G., Goecke, R. and Bartlett, M. (2014). A Discriminative Parts Based Model Approach for Fiducial Points Free and Shape Constrained Head Pose Normalisation In The Wild. IEEE Winter Conference on Applications of Computer Vision (WACV). (Acceptance Rate: 40%) [PDF]
  14. Sikka, K., Dykstra, K., Sathyanarayana, S., Littlewort, G. and Bartlett, M. (2013). Multiple Kernel Learning for Emotion Recognition in the Wild. Proceedings of the 15th ACM on International Conference on Multimodal Interaction (ICMI). EmotiW'13 Challenge. 'Best Paper Award'. (Oral Presentation) [PDF] [Slides] [Project Page]
  15. Sikka, K., Dhall, A., and Bartlett, M. (2013). Weakly Supervised Pain Localization using Multiple Instance Learning. IEEE International Conference on Automatic Face and Gesture Recognition (FG). 'Best Student Paper Honorable Mention Award'. (Acceptance Rate (Oral): 12%) [Project Page and videos] [PDF] [Slides]
  16. Sikka, K., Wu, T., Susskind, J., and Bartlett, M. (2012). Exploring Bag of Words Architectures in the Facial Expression Domain. European Conference on Computer Vision Workshops ( ECCVW). Lecture Notes in Computer Science, Springer. (Oral, Acceptance Rate: 33%) [PDF] [Slides] [ProjectPage]
  17. Singh, P. K., Sinha, N., Sikka, K., and Mishra, A. K. (2011). Texture information-based hybrid methodology for the segmentation of SAR images. International Journal of Remote Sensing (Taylor and Francis), 32(15), 4155-4173. (Impact Factor: 1.138) [PDF]
  18. Sikka, K., and Deserno, T. M. (2010). Comparison of algorithms for ultrasound image segmentation without ground truth. SPIE Medical Imagin, 7627, 76271C-76271C-9. [PDF]
  19. Sikka, K., Sinha, N., Singh, P. K., and Mishra, A. K. (2009). A fully automated algorithm under modified FCM framework for improved brain MR image segmentation. Magnetic resonance imaging (Elsevier), 27(7), 994-1004. (Impact factor: 2.060) [PDF]