Guillermo Reyes

Doctoral Researcher

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Research Interests

Computer VisionApplied Machine LearningContinuous LearningReinforcement LearningMulti-modal InteractionAttention GuidanceAutonomous Systems
 

Open Thesis Topics

Machine Learning, and Deep Learning, in particular, have improved the recognition of dynamic hand gestures in the past decadeDifferent architectures like CNNLSTMs [1], 3D Convolutional Networks [2], and others have been developed to approach this task. However, one of the problems that these architectures have, is that they require large amounts of data in order to produce high-performance models. This data might not be available in particular situations like different camera angles (e.g., top-down), or different types of cameras (e.g., time-of-flight cameras). While transfer learning can sometimes be used to reduce the amount of data required to train these models, the available pre-trained models may sometimes be unsuitable and not help solve the new task. An alternative to this is the use of synthetic data. By providing synthetic data that is similar to the one that is expected in the real world, the amount of new data that needs to be collected decreases. For this purpose, modern game engines and modeling software could be used to predefine the gestures and introduce small variation[3]. The aforementioned architectures could then use this data in combination with real-world gestures to train the gesture recognition model from scratch.  

 

Focus

The student will develop a dynamic gesture generation system using modern game engines like Unity3D or Unreal Engine. The evaluation of this system will depend on the type of thesis the student pursues (Bachelor’s or Master’s thesis). 

Prerequisites

The following are skills that you will probably need to successfully complete this thesis. Although some of these skills you’ll be able to pick along the way, the more you have at the beginning the betterIdeally you are: 

  • Familiar with game engines and programming (3D modelling and Shader programming are a plus) 

  • Familiar with deep learning concepts and python (for the evaluation.) 

  • Autodidact. Some skills you’ll have to learn along the way and will have to experiment quite a bit.  

If you are unsure about some of your skills but are interested in the topic just apply and we can have a chat.  

How to apply

Please email me with the following pieces of information: 

  • When you plan to start the thesis 

  • When you plan to finish the thesis 

  • A short motivational statement why this topic is interesting to you (max 250 words) 

  • A short summary of your experience with game engines and machine learning.  

  • Your transcript of records and CV 

 

 

 

 

Publications ()

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