Bare-hand Gesture Recognition and Tracking through the Large-scale Image Retrieval

The rapid development of mobile devices during the recent decade has been greatly driven by interaction and visualization technologies. Although touchscreens have signicantly enhanced the interaction technology, it is predictable that with the future mobile devices, e.g., augmentedreality glasses and smart watches, users will demand more intuitive in-puts such as free-hand interaction in 3D space. Specically, for manipulation of the digital content in augmented environments, 3D hand/body gestures will be extremely required. Therefore, 3D gesture recognition and tracking are highly desired features for interaction design in future smart environments. Due to the complexity of the hand/body motions, and limitations of mobile devices in expensive computations, 3D gesture analysis is still an extremely diffcult problem to solve.This thesis aims to introduce new concepts, theories and technologies for natural and intuitive interaction in future augmented environments. Contributions of this thesis support the concept of bare-hand 3D gestural interaction and interactive visualization on future smart devices. The introduced technical solutions enable an e ective interaction in the 3D space around the smart device. High accuracy and robust 3D motion analysis of the hand/body gestures is performed to facilitate the 3D interaction in various application scenarios. The proposed technologies enable users to control, manipulate, and organize the digital content in 3D space.