Cognitive behaviour analysis based on facial information using depth sensors

Montenegro, J.F., Villarini, B., Gkelias, A. and Argyriou, V. 2016. Cognitive behaviour analysis based on facial information using depth sensors. Wannous, H., Pala, P., Daoudi, M. and Flórez-Revuelta, F. (ed.) ICPR Workshop on Understanding Human Activities through 3D Sensors (UHA3DS 2016). Cancun, Mexico 04 - 08 Dec 2016 Springer. doi:10.1007/978-3-319-91863-1

TitleCognitive behaviour analysis based on facial information using depth sensors
AuthorsMontenegro, J.F., Villarini, B., Gkelias, A. and Argyriou, V.
EditorsWannous, H., Pala, P., Daoudi, M. and Flórez-Revuelta, F.
TypeConference paper
Abstract

Cognitive behaviour analysis is considered of high impor- tance with many innovative applications in a range of sectors including healthcare, education, robotics and entertainment. In healthcare, cogni- tive and emotional behaviour analysis helps to improve the quality of life of patients and their families. Amongst all the different approaches for cognitive behaviour analysis, significant work has been focused on emo- tion analysis through facial expressions using depth and EEG data. Our work introduces an emotion recognition approach using facial expres- sions based on depth data and landmarks. A novel dataset was created that triggers emotions from long or short term memories. This work uses novel features based on a non-linear dimensionality reduction, t-SNE, applied on facial landmarks and depth data. Its performance was eval- uated in a comparative study, proving that our approach outperforms other state-of-the-art features.

Keywordscognitive behaviour, depth sensors, dimensionality reduction
Year2016
ConferenceICPR Workshop on Understanding Human Activities through 3D Sensors (UHA3DS 2016)
PublisherSpringer
Accepted author manuscriptICPRWorkshopVACamera.pdf
Publication dates
Published16 May 2018
JournalLecture Notes in Computer Science
Journal citation10188, pp. 15-28
ISSN0302-9743
Book titleUnderstanding Human Activities Through 3D Sensors: Second International Workshop, UHA3DS 2016, Held in Conjunction with the 23rd International Conference on Pattern Recognition, ICPR 2016, Cancun, Mexico, December 4, 2016, Revised Selected Papers
ISBN9783319918624
Digital Object Identifier (DOI)doi:10.1007/978-3-319-91863-1
Web address (URL) of conference proceedingshttps://www.springer.com/gb/book/9783319918624?wt_mc=ThirdParty.RD.3.EPR653.About_eBook#otherversion=9783319918631
Web address (URL)http://www-rech.telecom-lille.fr/uha3ds2016/Papers/Cognitive%20behaviour%20analysis.pdf

Related outputs

Morphological and multi-level geometrical descriptor analysis in CT and MRI volumes for automatic pancreas segmentation
Asaturyan, H., Gligorievski, A. and Villarini, B. 2019. Morphological and multi-level geometrical descriptor analysis in CT and MRI volumes for automatic pancreas segmentation. Computerized Medical Imaging and Graphics. 75 (July 2019), pp. 1-13. doi:10.1016/j.compmedimag.2019.04.004

The SmartTarget BIOPSY trial: A prospective, within-person randomised, blinded trial comparing the accuracy of visual-registration and MRI/ultrasound image-fusion targeted biopsies for prostate cancer risk stratification
Hamid, S., Donaldson, I.A., Hu, Y., Rodell, R., Villarini, B., Bonmati, E., Tranter, P., Punwani, S., Side, H.S., Willis, S., van der Meulen, J., Hawkes, D., Mccarran, N., Potyka, I., Williams, N.W., Brew-Graves, C., Freeman, A., Moore, C.M., Barratt, D., Emberton, M. and Ahmed, H.U. 2019. The SmartTarget BIOPSY trial: A prospective, within-person randomised, blinded trial comparing the accuracy of visual-registration and MRI/ultrasound image-fusion targeted biopsies for prostate cancer risk stratification. European Urology. 75 (5), p. 733–740. doi:10.1016/j.eururo.2018.08.007

Hierarchical Framework for Automatic Pancreas Segmentation in MRI Using Continuous Max-flow and Min-Cuts Approach
Asaturyan, H. and Villarini, B. 2018. Hierarchical Framework for Automatic Pancreas Segmentation in MRI Using Continuous Max-flow and Min-Cuts Approach. ICIAR 2018 International Conference Image Analysis and Recognition. Póvoa de Varzim, Portugal 27 - 29 Jun 2018 Springer. doi:10.1007/978-3-319-93000-8_64

Technical Note: Error metrics for estimating the accuracy of needle/instrument placement during transperineal MR/US-guided prostate interventions
Bonmati, E., Hu, Y., Villarini, B., Rodell, R., Martin, P., Han, L., Donaldson, I., Ahmed, H.U., Moore, C.M., Emberton, M. and Barratt, D.C. 2018. Technical Note: Error metrics for estimating the accuracy of needle/instrument placement during transperineal MR/US-guided prostate interventions. Medical Physics. 45 (4), pp. 1408-1414. doi:10.1002/mp.12814

MP33-20 The SmartTarget Biopsy Trial: a Prospective Paired Blinded Trial with Randomisation to Compare Visual-Estimation and Image-Fusion Targeted Prostate Biopsies
Donaldson, I., Hamid, S., Barratt, D., Hu, Y., Rodell, R., Villarini, B., Bonmati, E., Martin, P., Hawkes, D., Mccarran, N., Potyka, I., Williams, N., Bre-Graves, C., Moore, C., Emberson, M. and Ahmed, H. 2017. MP33-20 The SmartTarget Biopsy Trial: a Prospective Paired Blinded Trial with Randomisation to Compare Visual-Estimation and Image-Fusion Targeted Prostate Biopsies. The Journal of Urology. 197 (4), p. e425. doi:10.1016/j.juro.2017.02.1016

A Framework for Morphological Feature Extraction of Organs from MR Images for Detection and Classification of Abnormalities
Villarini, B., Asaturyan, H., Thomas, E.L., Mould, R. and Bell, J.D. 2017. A Framework for Morphological Feature Extraction of Organs from MR Images for Detection and Classification of Abnormalities. Proceedings of the 30th IEEE International Symposium on Computer-Based Medical Systems (CBMS’17). Thessaloniki, Greece 22 - 24 Jun 2017 IEEE . doi:10.1109/CBMS.2017.49

Photometric Stereo for 3D Face Reconstruction Using Non Linear Illumination Models
Villarini, B., Gkelias, A. and Argyriou, V. 2016. Photometric Stereo for 3D Face Reconstruction Using Non Linear Illumination Models. ICPR Workshop on Multimodal Pattern Recognition of Social Signals in Human-Computer Interaction. Cancun, Mexico 04 Dec 2016 - 08 Jun 2017 Springer. doi:10.1007/978-3-319-59259-6_12

Validation of the needle targeting accuracy of a MRI/TRUS- image-guided system for transperineal prostate cancer biopsy
Bonmati, E., Hu, Y., Rodell, R., Villarini, B., Martin, P., Han, L., Donaldson, I., Ahmed, H.U., Moore, C.M., Emberton, M. and Barratt, D.C. 2015. Validation of the needle targeting accuracy of a MRI/TRUS- image-guided system for transperineal prostate cancer biopsy. CARS-Computer Assisted Radiology and Surgery, 29th International Congress and Exhibition. Barcelona, Spain 24 Jun 2015 Springer. doi:10.1007/s11548-015-1213-2

Image, video and 3D data registration: medical, satellite and video processing applications with quality metrics
Argyriou, V., Del Rincon, J.M., Villarini, B. and Roche, A. 2015. Image, video and 3D data registration: medical, satellite and video processing applications with quality metrics. Oxford Wiley.

A sparse representation method for determining the optimal illumination directions in Photometric Stereo
Argyriou, V., Zafeiriou, S., Villarini, B. and Petrou, M. 2013. A sparse representation method for determining the optimal illumination directions in Photometric Stereo. Signal Processing. 93 (11), pp. 3027-3038. doi:10.1016/j.sigpro.2013.04.026

An optimal method for searching UEP profiles in wireless JPEG 2000 video transmission
Baruffa, G., Frescura, F., Micanti, P. and Villarini, B. 2012. An optimal method for searching UEP profiles in wireless JPEG 2000 video transmission. ICIP - International Conference on Image Processing. Orlando, FL 30 Sep 2012 IEEE . doi:10.1109/ICIP.2012.6467192

A reduced-reference perceptual image and video quality metric based on edge preservation
Martini, M.G., Villarini, B. and Fiorucci, F. 2012. A reduced-reference perceptual image and video quality metric based on edge preservation. EURASIP Journal on Advances in Signal Processing. 2012 (66). doi:10.1186/1687-6180-2012-66

Image quality assessment based on edge preservation
Martini, M.G., Hewage, C. and Villarini, B. 2012. Image quality assessment based on edge preservation. Signal Processing: Image Communication. 27 (8), pp. 875-882. doi:10.1016/j.image.2012.01.012

Reduced-Reference Image Quality Assessment Based on Edge Preservation
Martini, M.G., Villarini, B. and Fiorucci, F. 2011. Reduced-Reference Image Quality Assessment Based on Edge Preservation. 7th International ICST Mobile Multimedia Communications Conference. Cagliari, Italy 05 Sep 2011 Springer. doi:10.1007/978-3-642-30419-4_3

A reprogrammable computing platform for JPEG 2000 and H.264 SHD video coding
Baruffa, G., Fiorucci, F., Frescura, F., Micanti, P., Verducci, L. and Villarini, B. 2010. A reprogrammable computing platform for JPEG 2000 and H.264 SHD video coding. 8th IEEE Workshop on Embedded Systems for Real-Time Multimedia (ESTIMedia). Scottsdale, AZ 28 Oct 2010 IEEE . doi:10.1109/ESTMED.2010.5666990

Permalink - https://westminsterresearch.westminster.ac.uk/item/q12ww/cognitive-behaviour-analysis-based-on-facial-information-using-depth-sensors


Share this
Tweet
Email