publication . Preprint . 2019

Prediction of gaze direction using Convolutional Neural Networks for Autism diagnosis

Núñez-Fernández, Dennis; Porras-Barrientos, Franklin; Vittet-Mondoñedo, Macarena; Gilman, Robert H.; Zimic, Mirko;
Open Access English
  • Published: 25 Oct 2019
Abstract
Autism is a developmental disorder that affects social interaction and communication of children. The gold standard diagnostic tools are very difficult to use and time consuming. However, diagnostic could be deduced from child gaze preferences by looking a video with social and abstract scenes. In this work, we propose an algorithm based on convolutional neural networks to predict gaze direction for a fast and effective autism diagnosis. Early results show that our algorithm achieves real-time response and robust high accuracy for prediction of gaze direction.
Subjects
Medical Subject Headings: genetic structures
ACM Computing Classification System: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
free text keywords: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction, Electrical Engineering and Systems Science - Image and Video Processing
Related Organizations
Download from

[1] Natacha Akshoomoff, Christina Corsello, and Heather Schmidt. The role of the autism diagnostic observation schedule in the assessment of autism spectrum disorders in school and community settings. The California school psychologist : CASP, 11:7-19, 2006. 17502922[pmid].

[2] American Psychiatric Association. Autism spectrum disorder. In: Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, American Psychiatric Association, Arlington, VA 2013. P, 50, 2013.

[3] Eunji Chong, Katha Chanda, Zhefan Ye, Audrey Southerland, Nataniel Ruiz, Rebecca M. Jones, Agata Rozga, and James M. Rehg. Detecting gaze towards eyes in natural social interactions and its use in child assessment. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 1(3):43:1-43:20, September 2017.

[4] Flavio Cunha and James Heckman. The technology of skill formation. American Economic Review, 97(2):31-47, May 2007.

[5] Orla Doyle, Colm P. Harmon, James J. Heckman, and Richard E. Tremblay. Investing in early human development: Timing and economic efficiency. Economics & Human Biology, 7(1):1 - 6, 2009.

[6] Centers for Disease Control and Prevention. Prevalence of autism spectrum disorders-autism and developmental disabilities monitoring network, united states, 2006. MMWR Surveillance Summaries, 58:1-20, 2009.

[7] Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell. Caffe: Convolutional architecture for fast feature embedding. In Proceedings of the 22Nd ACM International Conference on Multimedia, MM '14, pages 675-678, New York, NY, USA, 2014. ACM.

[8] Warren Jones, Katelin Carr, and Ami Klin. Absence of Preferential Looking to the Eyes of Approaching Adults Predicts Level of Social Disability in 2-Year-Old Toddlers With Autism Spectrum Disorder. JAMA Psychiatry, 65(8):946-954, 08 2008.

[9] Ami Klin, David J. Lin, Phillip Gorrindo, Gordon Ramsay, and Warren Jones. Two-year-olds with autism orient to non-social contingencies rather than biological motion. Nature, 459(7244):257-261, 2009. [OpenAIRE]

[10] Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278-2324, Nov 1998.

[11] Wenbo Liu, Ming Li, and Li Yi. Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework. Autism research : official journal of the International Society for Autism Research, 9, 04 2016.

[12] Karen Pierce, David Conant, Roxana Hazin, Richard Stoner, and Jamie Desmond. Preference for Geometric Patterns Early in Life as a Risk Factor for Autism. JAMA Psychiatry, 68(1):101-109, 01 2011.

[13] Karen Pierce, Steven Marinero, Roxana Hazin, Benjamin McKenna, Cynthia Carter Barnes, and Ajith Malige. Eye tracking reveals abnormal visual preference for geometric images as an early biomarker of an autism spectrum disorder subtype associated with increased symptom severity. Biological Psychiatry, 79(8):657-666, Apr 2016.

[14] P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, volume 1, pages I-I, Dec 2001.

Abstract
Autism is a developmental disorder that affects social interaction and communication of children. The gold standard diagnostic tools are very difficult to use and time consuming. However, diagnostic could be deduced from child gaze preferences by looking a video with social and abstract scenes. In this work, we propose an algorithm based on convolutional neural networks to predict gaze direction for a fast and effective autism diagnosis. Early results show that our algorithm achieves real-time response and robust high accuracy for prediction of gaze direction.
Subjects
Medical Subject Headings: genetic structures
ACM Computing Classification System: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
free text keywords: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction, Electrical Engineering and Systems Science - Image and Video Processing
Related Organizations
Download from

[1] Natacha Akshoomoff, Christina Corsello, and Heather Schmidt. The role of the autism diagnostic observation schedule in the assessment of autism spectrum disorders in school and community settings. The California school psychologist : CASP, 11:7-19, 2006. 17502922[pmid].

[2] American Psychiatric Association. Autism spectrum disorder. In: Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, American Psychiatric Association, Arlington, VA 2013. P, 50, 2013.

[3] Eunji Chong, Katha Chanda, Zhefan Ye, Audrey Southerland, Nataniel Ruiz, Rebecca M. Jones, Agata Rozga, and James M. Rehg. Detecting gaze towards eyes in natural social interactions and its use in child assessment. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 1(3):43:1-43:20, September 2017.

[4] Flavio Cunha and James Heckman. The technology of skill formation. American Economic Review, 97(2):31-47, May 2007.

[5] Orla Doyle, Colm P. Harmon, James J. Heckman, and Richard E. Tremblay. Investing in early human development: Timing and economic efficiency. Economics & Human Biology, 7(1):1 - 6, 2009.

[6] Centers for Disease Control and Prevention. Prevalence of autism spectrum disorders-autism and developmental disabilities monitoring network, united states, 2006. MMWR Surveillance Summaries, 58:1-20, 2009.

[7] Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell. Caffe: Convolutional architecture for fast feature embedding. In Proceedings of the 22Nd ACM International Conference on Multimedia, MM '14, pages 675-678, New York, NY, USA, 2014. ACM.

[8] Warren Jones, Katelin Carr, and Ami Klin. Absence of Preferential Looking to the Eyes of Approaching Adults Predicts Level of Social Disability in 2-Year-Old Toddlers With Autism Spectrum Disorder. JAMA Psychiatry, 65(8):946-954, 08 2008.

[9] Ami Klin, David J. Lin, Phillip Gorrindo, Gordon Ramsay, and Warren Jones. Two-year-olds with autism orient to non-social contingencies rather than biological motion. Nature, 459(7244):257-261, 2009. [OpenAIRE]

[10] Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278-2324, Nov 1998.

[11] Wenbo Liu, Ming Li, and Li Yi. Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework. Autism research : official journal of the International Society for Autism Research, 9, 04 2016.

[12] Karen Pierce, David Conant, Roxana Hazin, Richard Stoner, and Jamie Desmond. Preference for Geometric Patterns Early in Life as a Risk Factor for Autism. JAMA Psychiatry, 68(1):101-109, 01 2011.

[13] Karen Pierce, Steven Marinero, Roxana Hazin, Benjamin McKenna, Cynthia Carter Barnes, and Ajith Malige. Eye tracking reveals abnormal visual preference for geometric images as an early biomarker of an autism spectrum disorder subtype associated with increased symptom severity. Biological Psychiatry, 79(8):657-666, Apr 2016.

[14] P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, volume 1, pages I-I, Dec 2001.

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