In this study a new camera testing method is introduced to determine and analyze the autofocus latency of cameras. This analysis allows for objective comparison and tuning of autofocus algorithms in order to deliver both sharp images and the optimal user experience with a camera. Given images taken in variable illuminance conditions with different methods of focus reset, along with high-speed recordings of the camera viewfinder throughout the reset and capture, machine vision is used to extract three different types of latencies:

  • The first latency is the autofocus time, which is measured from the end of the focus reset to full stability, as measured by slanted-edge sharpness in the camera viewfinder.

  • The next latency is the user interface latency, which also comes from the viewfinder and is the time between the camera trigger and when the user interface of the camera indicates that a capture took place.

  • The final latency is the captured image latency, which is taken from the captured image itself and is the time between the camera trigger and when the image is actually captured.

In addition, we measure the sharpness of the final captured image in each test. Commercially available smartphone devices were tested using this method, showing significantly different results in both latency and sharpness measurements and uncovering trends in sharpness-latency trade-offs.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.