| 251. |
- Kuang, Yubin, et al.
(författare)
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Optimizing Visual Vocabularies Using Soft Assignment Entropies
- 2011
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Ingår i: Lecture Notes in Computer Science. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. - 9783642192814 - 9783642192821 ; 6495, s. 255-268
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Konferensbidrag (refereegranskat)abstract
- The state of the art for large database object retrieval in images is based on quantizing descriptors of interest points into visual words. High similarity between matching image representations (as bags of words) is based upon the assumption that matched points in the two images end up in similar words in hard assignment or in similar representations in soft assignment techniques. In this paper we study how ground truth correspondences can be used to generate better visual vocabularies. Matching of image patches can be done e.g. using deformable models or from estimating 3D geometry. For optimization of the vocabulary, we propose minimizing the entropies of soft assignment of points. We base our clustering on hierarchical k-splits. The results from our entropy based clustering are compared with hierarchical k-means. The vocabularies have been tested on real data with decreased entropy and increased true positive rate, as well as better retrieval performance.
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| 252. |
- Kuang, Yubin, et al.
(författare)
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Partial Symmetry in Polynomial Systems and Its Application in Computer Vision
- 2014
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Ingår i: [Host publication title missing]. - 1063-6919. ; , s. 438-445
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Konferensbidrag (refereegranskat)abstract
- Algorithms for solving systems of polynomial equations are key components for solving geometry problems in computer vision. Fast and stable polynomial solvers are essential for numerous applications e.g. minimal problems or finding for all stationary points of certain algebraic errors. Recently, full symmetry in the polynomial systems has been utilized to simplify and speed up state-of-the-art polynomial solvers based on Gr¨obner basis method. In this paper, we further explore partial symmetry (i.e. where the symmetry lies in a subset of the variables) in the polynomial systems. We develop novel numerical schemes to utilize such partial symmetry. We then demonstrate the advantage of our schemes in several computer vision problems. In both synthetic and real experiments, we show that utilizing partial symmetry allow us to obtain faster and more accurate polynomial solvers than the general solvers.
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| 253. |
- Kuang, Yubin, et al.
(författare)
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Pose Estimation with Unknown Focal Length using Points, Directions and Lines
- 2013
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Ingår i: [Host publication title missing]. ; , s. 529-536
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Konferensbidrag (refereegranskat)abstract
- In this paper, we study the geometry problems of estimating camera pose with unknown focal length using combination of geometric primitives. We consider points, lines and also rich features such as quivers, i.e. points with one or more directions. We formulate the problems as polynomial systems where the constraints for different primitives are handled in a unified way. We develop efficient polynomial solvers for each of the derived cases with different combinations of primitives. The availability of these solvers enables robust pose estimation with unknown focal length for wider classes of features. Such rich features allow for fewer feature correspondences and generate larger inlier sets with higher probability. We demonstrate in synthetic experiments that our solvers are fast and numerically stable. For real images, we show that our solvers can be used in RANSAC loops to provide good initial solutions.
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| 254. |
- Kuang, Yubin, et al.
(författare)
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Revisiting Trifocal Tensor Estimation Using Lines
- 2014
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Ingår i: Pattern Recognition (ICPR), 2014 22nd International Conference on. - 1051-4651. ; , s. 2419-2423
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Konferensbidrag (refereegranskat)abstract
- In this paper, we revisit the problem of estimating the trifocal tensor from image line measurements. With measurements of corresponding lines in three views, a linear method [1] requiring 13 lines was developed to estimate the trifocal tensor from which projective reconstruction of the scene is made possible. By further utilizing the nonlinear constraints on the trifocal tensor, we propose several new linear solvers that require fewer number of lines (10,11,12) than the previous linear method. We use methods based on algebraic geometry to incorporate the non-linear constraints in the estimation. We demonstrate the performance of the proposed solvers on synthetic data. We also test the solvers on real images and obtain promising results.
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| 255. |
- Kuang, Yubin, et al.
(författare)
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Single Antenna Anchor-Free UWB Positioning based on Multipath Propagation
- 2013
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Ingår i: [Host publication title missing].
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Konferensbidrag (refereegranskat)abstract
- Radio based localization and tracking usually require multiple receivers/transmitters or a known floor plan. This paper presents a method for anchor free indoor positioning based on single antenna ultra wideband (UWB) measurements. By using time of arrival information from multipath propagation components stemming from scatterers with different, but unknown, positions we estimate the movement of the receiver as well as the angle of arrival of the considered multipath components. Experiments are shown for real indoor data measured in a lecture room with promising results. Simultaneous estimation of both receiver motion, transmitter and scatterer positions is performed using an factorization based approach followed by non-linear least squares optimization. A RANSAC approach to automatic matching of data has also been implemented and tested. The resulting reconstruction is compared to ground truth motion as given by the antenna positioner. The resulting accuracy is in the order of one cm.
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| 256. |
- Kuang, Yubin, et al.
(författare)
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Stratified Sensor Network Self-Calibration From TDOA Measurements
- 2013
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Ingår i: [Host publication title missing].
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Konferensbidrag (refereegranskat)abstract
- This paper presents a study of the sensor network calibration time-difference-of-arrival (TDOA) measurements. Such calibration arise in several applications such as calibration of (acoustic or ultrasound) microphone arrays, bluetooth arrays, and radio antenna networks. We propose a non-iterative algorithm that apply a three-step stratification process, (i) using a set of rank constraints to determine the unknown offsets, (ii) applying factorization techniques to determine transmitters and receivers up to unknown affine transformation and (iii) determining the affine stratification using the remaining constraints. This results in novel algorithms for direct recovery of both transmitter and receiver positions using time-difference-of-arrival measurements, down to 6 receivers and 8 transmitters. Experiments are shown both for simulated and real data with promising results.
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| 257. |
- Kuang, Yubin, et al.
(författare)
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Supervised Feature Quantization with Entropy Optimization
- 2011
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Ingår i: Computer Vision Workshops (ICCV Workshops), 2011 IEEE International Conference on. - 9781467300629 ; , s. 1386-1393
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Konferensbidrag (refereegranskat)abstract
- Feature quantization is a crucial component for efficient large scale image retrieval and object recognition. By quantizing local features into visual words, one hopes that features that match each other obtain the same word ID. Then, similarities between images can be measured with respect to the corresponding histograms of visual words. Given the appearance variations of local features, traditional quantization methods do not take into account the distribution of matched features. In this paper, we investigate how to encode additional prior information on the feature distribution via entropy optimization by leveraging ground truth correspondence data. We propose a computationally efficient optimization scheme for large scale vocabulary training. The results from our experiments suggest that entropy-optimized vocabulary performs better than unsupervised quantization methods in terms of recall and precision for feature matching. We also demonstrate the advantage of the optimized vocabulary for image retrieval.
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| 258. |
- Kuang, Yubin, et al.
(författare)
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Understanding TOA and TDOA Network Calibration using Far Field Approximation as Initial Estimate
- 2012
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Ingår i: ICPRAM 2012 - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods, Volume 2. - 9789898425997 ; , s. 590-596
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Konferensbidrag (refereegranskat)abstract
- This paper presents a study of the so called far field approximation to the problem of determining both the direction to a number of transmittors and the relative motion of a single antenna using relative distance measurements. The same problem is present in calibration of microphone and wifi-transmittor arrays. In the far field approximation we assume that the relative motion of the antenna is small in comparison to the distances to the base stations. The problem can be solved uniquely with at least three motions of the antenna and at least six real or virtual transmittors. The failure modes of the problem is determined to be (i) when the antenna motion is planar or (ii) when the transmittor directions lie on a cone. We also study to what extent the solution can be obtained in these degenerate configurations. The solution algorithm for the minimal case can be extended to the overdetermined case in a straightforward manner. We also implement and test algorithms for non-linear optimization of the residuals. In experiments we explore how sensitive the calibration is with respect to different degrees of far field approximations of the transmittors and with respect to noise in the data.
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| 259. |
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| 260. |
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