Feature-Based Image Compression

Morozkin, Pavel; Swynghedauw, Marc; Trocan, Maria

doi:10.1007/978-3-319-75417-8_43

Cited by 1 publication

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Morozkin, Swynghedauw, & Trocan, 2018, March we proposed a deep learning method based on Artificial Neural Network (ANN) used as a function regression calculator. It consists in tuning the hyperparameters (Bergstra & Bengio, 2012;Bergstra, Bardenet, Bengio, & Kégl, 2011; Snoek, Larochelle, & Adams, 2012) of this network to relate the image of the pupils (inputs) to the 5 parameters of a geometrical ellipse (outputs).…”

Section: Eye Image Compression Alternative Approachesmentioning

confidence: 99%

“…We then use the output of ANN classification followed by image data compression and its transmission in compressed form for further processing. In the previous publication (Morozkin et al, 2018, March), we presented the classical eye image approach and the NN-based eye image compression approach, neural network construction and training as well as testing framework. It should be noted that based on the neural network (Demuth, Beale, De Jess, & Hagan, 2014) the ROI image blocks are classified into 2 classes (blocks contain/does not contain pupil edges).…”

Section: Eye Image Compression Alternative Approachesmentioning

confidence: 99%

See 1 more Smart Citation

Image compression in resource-constrained eye tracking devices

Morozkin

Swynghedauw²,

Trocan

2019

Journal of Information and Telecommunication

Self Cite

View full text Add to dashboard Cite

Resource-constrained embedded devices, operating with images, are becoming increasingly common. Examples include remote low-power smart sensors, wireless sensor networks, autonomous cameras, eye tracking devices, etc. The principal requirements of such devices are the operation in real time, low power, low heat as well as low MIPS. These requirements can be fulfilled with the use of approximated version of original image processing algorithms. The EyeDee™ embedded eye tracking solution (developed by SuriCog) is the world's first innovative solution using the eye as a real-time mobile digital cursor, while maintaining full mobility. Being an example of resourceconstrained embedded device, the system consists of a wearable device (Weetsy™ frame) capturing images on the human's eye and an embedded pre-processing device (Weetsy™ preprocessing board) sending these eye images over a transmission medium (wire/wireless transmission) to a remote processing unit for the further gaze reconstruction. This paper is aimed at introducing image compression approaches in the resourceconstrained devices in general and some of their implementation in the Weetsy™ pre-processing board in particular.

show abstract

Section: Eye Image Compression Alternative Approachesmentioning

confidence: 99%

Section: Eye Image Compression Alternative Approachesmentioning

confidence: 99%