In the area of human–computer interaction, contemporary head tracking systems are often used as camera-based mouse emulators. While head movement detection provides the basis for related mouse shifting and positioning, standard click actions are usually emulated using stillness counter techniques such as Dwell Click (DC). However, these techniques can be a source of enlarged interaction burden, as users often have to struggle with time-consuming repetitive UI actions. This paper proposes a novel version of Blink Click (BC) action called B2C, based on double eye blink detection, as a valuable supplement for faster mouse click emulation. The integration of the proposed BC action into an existing head tracking system is presented, and implementation issues are thoroughly analyzed. Usability testing of the proposed B2C interaction model, along with the already embedded DC model, has been carried out, providing both quantitative and qualitative outcomes. The results show efficiency improvement as well as a higher level of users’ satisfaction when using the proposed version of BC, thus making it a strong candidate to become a standard feature within the computer-vision-based mouse emulation.
