Robust real-time on-line camera tracking method

Abstract

The invention discloses a robust real-time on-line camera tracking method which comprises the following steps: estimating the posture of a camera and calculating and adding a key frame, wherein fast and general feature matching is adopted for the estimation of the posture of the camera, and the posture of the current frame can be estimated in a robust mode; and simultaneously tracking by means of the camera and establishing the scene mapping. By utilizing the robust real-time on-line camera tracking method, a more stable matching effect is generated under the condition of a larger scene or quick motion of the camera, and the limitation that the traditional camera tracking method is dependent on the partial matching is overcome. On the other hand, by utilizing the robust real-time on-line camera tracking method, the processing speed for the key frame is faster, so that more key frames can be contained in the scene, and the responding capability of a camera tracking algorithm for the problem that the camera is easy to fail in tracking when entering into an unknown scene is strengthened.

Description

technical field [0001] The invention belongs to the fields of computer vision and augmented reality, in particular to a real-time camera tracking method in an unknown scene. Background technique [0002] The goal of vision-based camera tracking is to estimate the pose of a camera relative to its surroundings (6 degrees of freedom parameter) from an input image sequence or real-time video. It is useful for many other computer vision applications such as 3D reconstruction, video registration and image enhancement. Traditionally, this problem has been addressed by offline structural methods for motion recovery. However, in some practical applications, such as augmented reality and autonomous navigation, real-time camera pose is a necessary prerequisite. In these cases, offline methods cannot meet the efficiency requirements, so online real-time camera tracking has received more attention in recent years. [0003] In recent years, simultaneous localization and mapping techniq...

AI Technical Summary

Problems solved by technology

However, the simultaneous localization and mapping techniques only apply less prior knowledge and also brings the robustness problem of camera tracking techniques.

[0004] The robustness problem of the traditional camera tracking method mainly exists in the lack of resistance to three common problems in practical applications: (1) fast camera movement; (2) image blur caused by camera movement; (3) camera jitter

Questions 1 and 3 essentially stem from the same reason, that is, the camera tracking technology assumes continuity between the upper and lower frames.

In problem 1 and problem 3, since the motion of the camera does not strictly obey the motion model, it is likely to cause the failure of camera tracking

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