Designing a natural, usable, and efficient gesture-based virtual locomotion interface in immersive environments has been challenging. Freehand-based virtual locomotion technique (VLT) has the advantage of eliminating the need to see the handhold devices and has been implemented in many applications.Translation control and direction control are two essential components of freehand-based VLT; however, the transfer function of turning speed in direction control has not been well explored. In this article, we systematically investigate the effects of turning speed on freehand-based virtual locomotion for the first time. A transfer function that maps the position of the hand to the turning speed is defined, and three parameters related to the turning speed are investigated. In the experiment, participants are asked to travel in the virtual environment from a first-person perspective with different parameters. Statistical analysis of the experimental results reveals the relationship between the turning speed and the traveling performance as well as the traveling experience.
Dynamic hand gesture acting as a semaphoric gesture is a practical and intuitive mid-air gesture interface. Nowadays benefiting from the development of deep convolutional networks, the gesture recognition has already achieved a high accuracy, however, when performing a dynamic hand gesture such as gestures of direction commands, some unintentional actions are easily misrecognized due to the similarity of the hand poses. This hinders the application of dynamic hand gestures and cannot be solved by just improving the accuracy of the applied algorithm on public datasets, thus it is necessary to study such problems from the perspective of human-computer interaction. In this article, two methods are proposed to avoid misrecognition by introducing activation delay and using asymmetric gesture design. Firstly the temporal process of a dynamic hand gesture is decomposed and redefined, then a realtime dynamic hand gesture recognition system is built through a two-dimensional convolutional neural network. In order to investigate the influence of activation delay and asymmetric gesture design on system performance, a user study is conducted and experimental results show that the two proposed methods can effectively avoid misrecognition. The two methods proposed in this article can provide valuable guidance for researchers when designing realtime recognition system in practical applications.
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