Simultaneous positioning and map building method

Abstract

The invention discloses a simultaneous positioning and map building method which can reliably handle strong rotation and fast movement. The method proposes a simultaneous positioning and map building algorithm framework based on key frames, which can support fast local map expansion. In this framework, a new feature tracking method based on multiple homography matrix is proposed, which is efficient and robust under strong rotation and fast motion. A camera orientation optimization framework based on a sliding window is also proposed, and motion constraints are added between successive frames with simulated or actual IMU data. Finally, a method of obtaining the real scale of a specific plane and scene is proposed, so that a virtual object is placed on the specific plane in real size.

Description

technical field [0001] The invention relates to a monocular camera tracking method applicable to augmented reality, in particular to a robust camera tracking method based on key frames. Background technique [0002] In recent years, with the popularity of mobile terminals and wearable devices, augmented reality has gained unprecedented attention. Realistic augmented reality requires precise estimation of camera orientation and real-time reconstruction of the scene, which is also the problem to be solved by simultaneous localization and mapping (SLAM) technology. [0003] Due to the complexity of real-world scenarios, traditional SLAM methods do not work well in practical applications. For example, when a new user uses a mobile device to take a scene and watch an augmented reality effect, they tend to move and rotate the mobile device at will. Therefore, strong rotation and fast motion are very common, but state-of-the-art SLAM systems are also difficult to handle such comp...

AI Technical Summary

Problems solved by technology

However, strong rotation and fast motion violate the assumption of smooth motion

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