No abstract

No abstract

Large-screen human-computer interaction technology is reflected in all aspects of daily life. The dynamic gesture tracking algorithm commonly used in recent large-screen interactive technologies demonstrates compelling results but suffers from accuracy and real-time problems. This paper systematically addresses these issues by a switching federated filter method that combines particle filtering and Mean Shifting algorithms based on a 3D sensor. Compared with several algorithms, the results show that the one-hand and two-hand large-screen gesture tracking based on the switched federated filtering algorithm work well, and there is no tracking failure and loss of target. Therefore, the switching federated tracking positioning algorithm can be well applied to the design of human-computer interaction system and provide new ideas for future human-computer interaction.

No abstract

Aiming at its shortcomings of being difficult-to-move, low-efficiency modeling and high cost, this paper proposes a handheld 3D reconstruction system based on closed-loop detection and nonlinear optimization. The proposed system adds closed-loop detection with the bag of words model, reducing the drift and misalignment of the 3D reconstruction model caused by cumulative errors. Meanwhile, the g2o framework is employed to optimize the graph to solve the pose state estimation problem of the nonlinear system, which greatly enhances the robustness and accuracy of the system. The experimental platform for the experiment and analysis of the 3D reconstruction system uses a non-invasive 3D detection Tango mobile phone. Experimental results show that the indoor high-precision 3D reconstruction system based on the handheld device (Project Tango) has good accuracy and robustness, and the error range is about 1%. Therefore, the system proposed in this paper has a good application value.