Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Saliency, Scale and Image Description
International Journal of Computer Vision
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Localization of Ground Targets Using a Flying Sensor Network
SUTC '06 Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing -Vol 1 (SUTC'06) - Volume 01
Vision-based Target Geo-location using a Fixed-wing Miniature Air Vehicle
Journal of Intelligent and Robotic Systems
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
A subsumptive, hierarchical, and distributed vision-based architecture for smart robotics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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We propose a robust and accurate method for multi-target geo-localization from airborne video. The difference between our approach and other approaches in the literature is fourfold: 1) it does not require gimbal control of the camera or any particular path planning control for the UAV; 2) it can instantaneously geolocate multiple targets even if they were not previously observed by the camera; 3) it does not require a geo-referenced terrain database nor an altimeter for estimating the UAV's and the target's altitudes; and 4) it requires only one camera, but it employs a multi-stereo technique using the image sequence for increased accuracy in target geo-location. The only requirements for our approach are: that the intrinsic parameters of the camera be known; that the on board camera be equipped with global positioning system (GPS) and inertial measurement unit (IMU); and that enough feature points can be extracted from the surroundings of the target. Since the first two constraints are easily satisfied, the only real requirement is regarding the feature points. However, as we explain later, this last constraint can also be alleviated if the ground is approximately planar. The result is a method that can reach a few meters of accuracy for an UAV flying at a few hundred meters above the ground. Such performance is demonstrated by computer simulation, in-scale data using a model city, and real airborne video with ground truth.