Proceedings Article | 14 May 2018
KEYWORDS: Image compression, Facial recognition systems, Image processing, Image quality, Machine vision, Computer vision technology, Machine learning, Human vision and color perception, Mobile devices, Clouds
Image Processing and Computer Vision solutions have become commodities for software developers, thanks to the growing availability of Application Programming Interfaces (APIs) that encapsulate rich functionality, powered by advanced algorithms. Tech giants like Apple, Google, IBM, and Microsoft have made APIs and micro-services available in the cloud for the agile integration of machine learning and intelligent features onto everyday applications. As privacy and cyber welfare become prime concerns, special efforts have been devoted in the field of face processing and recognition. In this context, this paper provides a friendly, intuitive and fun to use mobile app that leverages the state-of-the-art APIs for face, age, gender and emotion recognition. The Face- It-Up app was implemented for the iOS platform and uses the Microsoft Cognitive Services APIs as a tool for human vision and face processing research. Experimental work on image compression, upside-down orientation, the Thatcher effect, negative inversion, high frequency, facial artifacts, caricatures and image degradation were performed to test the application. For this purpose, we used the Radboud and 10k US Adult Faces Databases. The app benefits from accessing high-resolution imagery and touch input from the smart-devices, allowing for a wide range of new experiments from the user perspective. Furthermore, our approach serves as a potential framework for new initiatives in image-based biometrics, the Internet of Things, and citizen science.
