With the development of various autofocusing (AF) technologies, sensor manufacturers are demanded to evaluate their performance accurately. The basic method of evaluating AF performance is to measure the time to get the refocused image and the sharpness of the image while repeatedly inducing the refocusing process. Traditionally, this process was conducted manually by covering and uncovering an object or sensor repeatedly, which can lead to unreliable results due to the human error and light blocking method. To deal with this problem, we propose a new device and solutions using a transparent display. Our method can provide more reliable results than the existing method by modulating the opacity, pattern, and repetition cycle of the target on the transparent display.
Video capture is becoming more and more widespread. The technical advances of consumer devices have led to improved video quality and to a variety of new use cases presented by social media and artificial intelligence applications. Device manufacturers and users alike need to be able to compare different cameras. These devices may be smartphones, automotive components, surveillance equipment, DSLRs, drones, action cameras, etc. While quality standards and measurement protocols exist for still images, there is still a need of measurement protocols for video quality. These need to include parts that are non-trivially adapted from photo protocols, particularly concerning the temporal aspects. This article presents a comprehensive hardware and software measurement protocol for the objective evaluation of the whole video acquisition and encoding pipeline, as well as its experimental validation.