Feature Tracking for Mobile Augmented Reality Using Video Coder Motion Vectors

Authors:
Gabriel Takacs;Vijay Chandrasekhar;Bernd Girod;Radek Grzeszczuk
Affiliations:
Information Systems Laboratory, Stanford University;Information Systems Laboratory, Stanford University;Information Systems Laboratory, Stanford University;Nokia Research Center, Palo Alto
Venue:
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Year:
2007

Citing 5
Cited 3

A Motion-Stabilized Outdoor Augmented Reality System

VR '99 Proceedings of the IEEE Virtual Reality
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Multi-Image Matching Using Multi-Scale Oriented Patches

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Going out: robust model-based tracking for outdoor augmented reality

ISMAR '06 Proceedings of the 5th 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

Hybrid tracking and visual search

MM '08 Proceedings of the 16th ACM international conference on Multimedia
Outdoors augmented reality on mobile phone using loxel-based visual feature organization

MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Object tracking in surveillance videos using compressed domain features from scalable bit-streams

Image Communication

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose a novel, low-complexity, tracking scheme that uses motion vectors directly from a video coder. We compare our tracking algorithm against ground truth data, and show that we can achieve a high level of accuracy, even though the motion vectors are rate-distortion optimized and do not represent true motion. We develop a framework for tracking in video sequences with various GOP structures. Such a scheme would find applications in the context of Mobile Augmented Reality. The proposed feature tracking algorithm can significantly reduce the required rate of feature extraction and matching.