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Orientation (computer vision)

About: Orientation (computer vision) is a research topic. Over the lifetime, 17196 publications have been published within this topic receiving 358181 citations.


Papers
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Journal ArticleDOI
TL;DR: A fast calibration method for computing the position and orientation of 2-D ultrasound images in 3-D space where a position sensor is mounted on the US probe, based on a custom-built phantom.
Abstract: We have developed a fast calibration method for computing the position and orientation of 2-D ultrasound (US) images in 3-D space where a position sensor is mounted on the US probe. This calibration is required in the fields of 3-D ultrasound and registration of ultrasound with other imaging modalities. Most of the existing calibration methods require a complex and tedious experimental procedure. Our method is simple and it is based on a custom-built phantom. Thirty N-fiducials (markers in the shape of the letter “N”) embedded in the phantom provide the basis for our calibration procedure. We calibrated a 3.5-MHz sector phased-array probe with a magnetic position sensor, and we studied the accuracy and precision of our method. A typical calibration procedure requires approximately 2 min. We conclude that we can achieve accurate and precise calibration using a single US image, provided that a large number (approximately ten) of N-fiducials are captured within the US image, enabling a representative sampling of the imaging plane. (E-mail: ykim@u.washington.edu)

117 citations

Journal ArticleDOI
TL;DR: Experimental results over a set of real-world sequences show that the proposed feature weighting procedure outperforms state-of-the-art solutions and thatThe proposed adaptive multifeature tracker improves the reliability of the target estimate while eliminating the need of manually selecting each feature's relevance.
Abstract: In this paper, we propose a tracking algorithm based on an adaptive multifeature statistical target model. The features are combined in a single particle filter by weighting their contributions using a novel reliability measure derived from the particle distribution in the state space. This measure estimates the reliability of the information by measuring the spatial uncertainty of features. A modified resampling strategy is also devised to account for the needs of the feature reliability estimation. We demonstrate the algorithm using color and orientation features. Color is described with partwise normalized histograms. Orientation is described with histograms of the gradient directions that represent the shape and the internal edges of a target. A feedback from the state estimation is used to align the orientation histograms as well as to adapt the scales of the filters to compute the gradient. Experimental results over a set of real-world sequences show that the proposed feature weighting procedure outperforms state-of-the-art solutions and that the proposed adaptive multifeature tracker improves the reliability of the target estimate while eliminating the need of manually selecting each feature's relevance.

116 citations

Journal ArticleDOI
01 Nov 1999
TL;DR: A method is presented to measure the magnetic fields generated from the eddy currents for each of three orthogonal gradient pulse vectors, and then to ascertain the image distortion that occurs in subsequent diffusion-weighted images with arbitrary gradient pulse vector amplitude and direction.
Abstract: Diffusion-weighted echo-planar magnetic resonance imaging is potentially of great importance as a diagnostic imaging tool; however, the technique currently suffers a number of limitations, including the image distortion caused by the eddy current induced fields when the diffusion-weighting magnetic field gradient pulses are applied. The distortions cause mis-registration between images with different diffusion-weighting, that then results in artifacts in quantitative diffusion images. A method is presented to measure the magnetic fields generated from the eddy currents for each of three orthogonal gradient pulse vectors, and then to use these to ascertain the image distortion that occurs in subsequent diffusion-weighted images with arbitrary gradient pulse vector amplitude and direction, and image plane orientation. The image distortion can then be reversed. Both temporal and spatial dependence of the residual eddy current induced fields are included in the analysis. Image distortion was substantially reduced by the correction scheme, for arbitrary slice position and angulation. This method of correction is unaffected by the changes in image contrast that occur due to diffusion weighting, and does not need any additional scanning time during the patient scan. It is particularly suitable for use with single-shot echo planar imaging.

116 citations

Journal ArticleDOI
TL;DR: The authors' proposed algorithm considers line fits in both FOV directions and gives a globally consistent set of expansion coefficients and an optimal image center, which provides more exhaustive FOV correction than previously proposed algorithms.
Abstract: Modern video based endoscopes offer physicians a wide-angle field of view (FOV) for minimally invasive procedures, Unfortunately, inherent barrel distortion prevents accurate perception of range. This makes measurement and distance judgment difficult and causes difficulties in emerging applications, such as virtual guidance of endoscopic procedures. Such distortion also arises in other wide FOV camera circumstances. This paper presents a distortion correction technique that can automatically calculate correction parameters, without precise knowledge of horizontal and vertical orientation. The method is applicable to any camera-distortion correction situation. Based on a least-squares estimation, the authors' proposed algorithm considers line fits in both FOV directions and gives a globally consistent set of expansion coefficients and an optimal image center. The method is insensitive to the initial orientation of the endoscope and provides more exhaustive FOV correction than previously proposed algorithms. The distortion-correction procedure is demonstrated for endoscopic video images of a calibration test pattern, a rubber bronchial training device, and real human circumstances. The distortion correction is also shown as a necessary component of an image-guided virtual-endoscopy system that matches endoscope images to corresponding rendered three-dimensional computed tomography views.

116 citations

Journal ArticleDOI
TL;DR: In this article, curved Gabor filters are applied to the curved ridge and valley structure of low-quality fingerprint images for the purpose of enhancing curved structures in noisy images, which locally adapt their shape to the direction of flow.
Abstract: Gabor filters play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved Gabor filters which locally adapt their shape to the direction of flow. These curved Gabor filters enable the choice of filter parameters which increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved Gabor filters are applied to the curved ridge and valley structure of low-quality fingerprint images. First, we combine two orientation field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation and they are used for estimating the local ridge frequency. Lastly, curved Gabor filters are defined based on curved regions and they are applied for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison to state-of-the-art enhancement methods.

116 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202212
2021535
2020771
2019830
2018727
2017691