Keyframe-Based Real-Time Camera Tracking

Zilong Dong1             Guofeng Zhang1             Jiaya Jia2             Hujun Bao1
1State Key Lab of CAD&CG, Zhejiang University                        2The Chinese University of Hong Kong


Abstract-We present a novel keyframe selection and recognition method for robust markerless real-time camera tracking. Our system contains an offline module to select features from a group of reference images and an online module to match them to the input live video in order to quickly estimate the camera pose. The main contribution lies in constructing an optimal set of keyframes from the input reference images, which are required to approximately cover the entire space and at the same time minimize the content redundancy amongst the selected frames. This strategy not only greatly saves the computation, but also helps reduce significantly the number of repeated features so as to improve the camera tracking quality. Our system also employs a parallel-computing scheme with the popular multi-CPU hardware architecture. Experimental results show that our method dramatically enhances the computing efficiency and eliminates the jittering artifact.

Publication:

Keyframe-Based Real-Time Camera Tracking
Zilong Dong, Guofeng Zhang, Jiaya Jia, and Hujun Bao.
IEEE International Conference on Computer Vision (ICCV), 2009.

BibTex:

@inproceedings{dong2009keyframe,
author = {Zilong Dong and Guofeng Zhang and Jiaya Jia and Hujun Bao},
title = {Keyframe-Based Real-Time Camera Tracking},
booktitle = {ICCV},
year = {2009}
}

 


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Test Sequences

Cubicle sequence

Campus sequence 1

Campus sequence 2

offline sequence

online sequence

offline sequence

online sequence

offline sequence

online sequence