Head Pose Estimation for Car Drivers

Shbib, Reda; Zhou, Shikun; Ndzi, David; Alkadhimi, Khalil Ibrahim Hady

doi:10.14257/ijunesst.2014.7.4.33

Cited by 1 publication

(1 citation statement)

References 9 publications

(11 reference statements)

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“…The latter approach uses information of the entire facial region and a separate detector is trained for different poses. Examples of model-based approaches are (Pyun et al, 2014;Shbib et al, 2014) where they first detect the face and search for features that correspond to essential points within that region (e.g. mouth, nose and eyes).…”

Section: Related Workmentioning

confidence: 99%

Fast and Accurate Face Orientation Measurement in Low-resolution Images on Embedded Hardware

Hulens

Beeck

Goedemé

2016

Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

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In numerous applications it is important to collect information about the gaze orientation or head-angle of a person. Examples are measuring the alertness of a car driver to see if he is still awake, or the attentiveness of people crossing a street to see if they noticed the cars driving by. In our own application we want to apply cinematographic rules (e.g. the rule of thirds where a face should be positioned left or right in the frame depending on the gaze direction) on images taken from an Unmanned Aerial Vehicle (UAV). For this an accurate estimation of the angle of the head is needed. These applications should run on embedded hardware so that they can be easily attached to e.g. a car or a UAV. This implies that the head angle detection algorithm should run in real-time on minimal hardware. Therefore we developed an approach that runs in real-time on embedded hardware while achieving excellent accuracy. We demonstrated these approaches on both a publicly available face dataset and our own dataset recorded from a UAV.

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Section: Related Workmentioning

confidence: 99%