Real-Time Visual Tracking of Complex Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Stable Real-Time 3D Tracking Using Online and Offline Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Monocular model-based 3D tracking of rigid objects
Foundations and Trends® in Computer Graphics and Vision
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Evaluation of Interest Point Detectors and Feature Descriptors for Visual Tracking
International Journal of Computer Vision
Towards feature-based situation assessment for airport apron video surveillance
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
Multiple 3D object position estimation and tracking using double filtering on multi-core processor
Multimedia Tools and Applications
Efficient keyframe-based real-time camera tracking
Computer Vision and Image Understanding
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We present a method that is able to track several 3D objects simultaneously, robustly, and accurately in real-time. While many applications need to consider more than one object in practice, the existing methods for single object tracking do not scale well with the number of objects, and a proper way to deal with several objects is required. Our method combines object detection and tracking: Frame-to-frame tracking is less computationally demanding but is prone to fail, while detection is more robust but slower. We show how to combine them to take the advantages of the two approaches, and demonstrate our method on several real sequences.