Due to the rapid growth of consumer grade devices and corresponding application market, the incorporation of vision capabilities into embedded systems has gained significant attention from researchers lately. Similarly to the human visual system, embedded computer vision systems analyze and extract information from visual content in a wide variety of products. Face recognition has […]

  Skin-tone detection has received considerable attention in recent years and applied in wide range of image processing and computer vision applications. The objective of this research project is to develop a real-time skin-tone detection solution optimized for consumer devices, allows for a deliverance of high detection performance at minimal computational costs. The proposed solution […]

Conventional camera sensors record three color channels: red, green and blue. In this project we will investigate computational photography algorithms for cameras that record a near-infrared channel (NIR) in addition to RGB. This channel is particularly useful for biometric imaging and holds great potential in consumer imaging applications as well. The key challenge in simultaneously […]

The fellowship mainly investigates an analysis of the state-of-the-art approaches, design and implementation of cutting-edge deep neural network models to be used on a mobile platform. It explored ways to optimize the deployment of these machine-learning models for prediction tasks on the mobile devices which requires energy efficiency and accuracy.

More than 25% of the fatal and injury car crashes are related to fatigue or drowsiness. This calls for the need for designing automated driver monitoring systems, which can continuously measure the drivers’ vigilance level and alert them if their cognitive state is not safe for driving anymore. One of the most reliable solutions is […]

Driver distraction has long been a critical issue drawing substantial amount of research effort. In order to reduce driver distraction for improved driving performance and safety, automotive suppliers have been endeavoring to provide optimum user interaction solutions. Until recent years, there have been growing interests in the use of gestural interfaces for in-vehicle information systems; […]

Optimizing a program for Graphics Processing Units (GPUs) is critical for performance, yet remains a challenge due to the non-intuitive interactions among the optimizations and the GPU architecture. Automatic optimization tuning for a GPU is demanding particularly given the exploding number of mobile GPU variants in the market. We explore the use of machine learning […]