View source for Visual analysis for infotainment in car interiors

{{StudentProjectTemplate
|Title=Driver-machine interfaces by cameras
|Summary=Visual analysis to steer infotainment in car interiors
|Author=Josef Bigun, Maycel Isaac Faraj
|Supervisor=Josef Bigun, Stefan Karlsson, Maycel Isaac Faraj
|Level=Master
|Status=Open
}}
As infotainment systems in vehicles become increasingly advanced, they will require more driver attention, affecting safety negatively. To keep the driver awareness focused on driving, sensors such as cameras need to be integrated into the driver support system of the vehicle. This master thesis will study real image data (extracted during driving in pre-product Volvo cars) with available machine vision methods to extract inputs from the driver. 

The goal is to investigate what informations can be extracted realistically to steer infotainment system without that the driver deviates her/his attention from driving, e.g. face tracking such that eyes and mouth are constantly under observation to obtain messages by lip-motion, decoding lip-motion, tracking hands of the driver.