Winect

WiFi human sensing has become increasingly attractive in enabling emerging human-computer interaction applications. The corresponding technique has gradually evolved from the classification of multiple activity types to more fine-grained tracking of 3D human poses. However, existing WiFi-based 3D human pose tracking is limited to a set of predefined activities. In this work, we present Winect, a 3D human pose tracking system for free-form activity using commodity WiFi devices. Our system tracks free-form activity by estimating a 3D skeleton pose that consists of a set of joints of the human body. In particular, we combine signal separation and joint movement modeling to achieve free-form activity tracking. Our system first identifies the moving limbs by leveraging the two-dimensional angle of arrival of the signals reflected off the human body and separates the entangled signals for each limb. Then, it tracks each limb and constructs a 3D skeleton of the body by modeling the inherent relationship between the movements of the limb and the corresponding joints. Our evaluation results show that Winect is environment-independent and achieves centimeter-level accuracy for free-form activity tracking under various challenging environments including the none-line-of-sight (NLoS) scenarios.

3D Modeling Design of Multirole Virtual Character Based on Visual Communication in Wireless Sensor Networks

In order to solve the problems of poor design effect and time consumption of traditional virtual character modeling design methods, a three-dimensional (3D) modeling design method of multirole virtual characters based on visual communication is studied. Firstly, the wireless sensor network is used to locate, scan, and collect the human body structure information and convert the coordinates to bind the 3D skeleton. Secondly, according to different human postures, we switch the linear hybrid skin algorithm, spherical hybrid skin algorithm, and double quaternion hybrid skin algorithm; design the geometric surface; and attach it to the 3D skeleton to generate 3D modeling. Finally, based on the influence of visual communication on human eye observation and psychological feeling, the geometric surface is divided twice, and the virtual character is rendered in the way of display, coating, and splicing to obtain a complete 3D modeling of the virtual character. The results show that the positioning coverage of this method is higher, the rendering effect of the hand and head is better, the design time is significantly shortened, and the maximum time is no more than 35 min.