Collateral effects of the Kalman Filter on the Throughput of a Head-Tracker for Mobile Devices

Abstract

We have developed an image-based head-tracker interface for mobile devices that uses the information of the front camera to detect and track the user’s nose position and translate its movements into a pointing metaphor to the device. However, as already noted in the literature, the measurement errors of the motion tracking leads to a noticeable jittering of the perceived motion. To counterbalance this unpleasant and unwanted behavior, we have applied a Kalman filter to smooth the obtained positions. In this paper we focus on the effect that the use of a Kalman filter can have on the throughput of the interface. Throughput is the human performance measure proposed by the ISO 9241-411 for evaluating the efficiency and effectiveness of non-keyboard input devices. The softness and precision improvements that the Kalman filter infers in the tracking of the cursor are subjectively evident. However, its effects on the ISO’s throughput have to be measured objectively to get an estimation of the benefits and drawbacks of applying a Kalman filter to a pointing device.