Image compression in resource-constrained eye tracking devices* * This paper is an extension of paper titled ‘Feature-based Image Compression’ (Morozkin et al., 2018, March), which was previously published in ACIIDS 2018 proceedings. This paper adds sections describing resource-constrained aspect of target devices as well as generalizes image compression approach design and implementation in the resource-constrained devices.View all notes

ABSTRACT 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 resource-constrained 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？ pre-processing 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 resource-constrained devices in general and some of their implementation in the Weetsy？ pre-processing board in particular