Computer Vision, Machine Learning, Evolutionary Optimization

[Assistant Professor] Vijay John

Basic Information


Doctor of Philosophy

Laboratory Name

Research Center for Smart Vehicles

Research Fields

Computer Vision, Machine Learning, Evolutionary Optimization

Academic Background

Ph.D. degree in computer vision and machine learning from University of Dundee in 2011.

Work History

Toyota Technological Institute, Nagoya, Japan
Assistant Professor
July 2017 - present

Commissioned Scientist
Feb 2017 - June 2017

Post-doctoral researcher
Feb 2014 - Feb 2017

University of Amsterdam, Amsterdam, The Netherlands
Post-doctoral researcher
2011 - 2013

Philips Research, Eindhoven, The Netherlands
Visiting researcher
Summer, 2012

Research Themes

Perception for Autonomous Vehicles
Sensor Fusion and Calibration
Predictive Behavior Analysis
Automated Driving


Best Image Processing Oral Presentation: V. John, A. Boyali and S. Mita, “Gabor Filter and Gershgorin Disk-based Convolutional Filter Constraining for Image Classification”, International Conference of Robotics and Automation Systems, 2017.

Best Image Processing Oral Presentation: V. John, L. Zheming and S. Mita. 2016. Robust Traffic Light and Arrow Detection using Optimal Camera Parameters and GPS-based Prior, IEEE Asia-Pacific Conference on Intelligent Robot Systems.

Toyoda Award for the Best Researcher: V. John. Deep learning for Intelligent Vehicle Applications. 2016.

Best Application Paper Award: V. John, Z. Liu, C. Guo, S. Mita and K. Kidono. 2015. RealTime Lane Estimation using Deep Features and Extra Trees Regression, Pacific Rim Symposium on Image and Video Technology.

Nvidia Award for Best Poster: V. John, Z. Liu and S. Mita. 2015. Deep learning-based real-time lane detection for intelligent vehicles. GPU Tech conference, Tokyo, Japan.

Invited Best Paper: V. John, Q. Long, Z. Liu and S. Mita. 2015. Automatic Calibration and Registration of Lidar and Stereo Camera without Calibration Objects. IEEE International Conference on Vehicular Electronics and Safety, Yokohama, Japan.

Best Paper Award: V. John, E. Trucco and S. McKenna. 2010. Marker-less Human Motion
Capture using Charting and Manifold Constrained Particle Swarm Optimisation. British Machine Vision Conference Student Workshop.

Invited Book Chapter: V. John, S. Ivekovic and E. Trucco. 2010. Markerless Human Motion Capture using Hierarchical Particle Swarm Optimisation. Chapter in Computer Vision, Imaging and Computer Graphics: Theory and Applications, Communications in Computer and Information Science, volume 68, 2010.

University of Dundee Discovery Scholarship: Awarded the Scholarship, in addition to the research council (EPSRC) studentship, (total scholarship valued at £65000) for my PhD research.

Research Scholarship: Awarded 50% scholarship to pursue Masters in Robotics at Carnegie Mellon University.

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