| 1. |
- Felsberg, Michael, 1974-
(författare)
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On Second Order Operators and Quadratic Operators
- 2008
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Ingår i: Proceedings - International Conference on Pattern Recognition. - : IEEE. - 9781424421756 - 9781424421749 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- In pattern recognition, computer vision, and image processing, many approaches are based on second order operators. Well-known examples are second order networks, the 3D structure tensor for motion estimation, and the Harris corner detector. A subset of second order operators are quadratic operators. It is lesser known that every second order operator can be written as a weighted quadratic operator. The contribution of this paper is to propose an algorithm for converting an arbitrary second order operator into a quadratic operator. We apply the method to several examples from image processing and machine learning. The advantages of the alternative implementation by quadratic operators is two-fold: The underlying linear operators allow new insights into the theory of the respective second order operators and replacing second order networks with sums of squares of linear networks reduces significantly the computational burden when the trained network is in operation phase.
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| 2. |
- Leinhard, Olof Dahlqvist, et al.
(författare)
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Quantitative Abdominal Fat Estimation Using MRI
- 2008
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Ingår i: Proceedings - International Conference on Pattern Recognition. - : IEEE Computer Society. - 9781424421749 - 9781424421756 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- This paper introduces a new method for automaticquantification of subcutaneous, visceral and nonvisceralinternal fat from MR-images acquired usingthe two point Dixon technique in the abdominal region.The method includes (1) a three dimensionalphase unwrapping to provide water and fat images, (2)an image intensity inhomogeneity correction, and (3) amorphon based registration and segmentation of thetissue. This is followed by an integration of the correctedfat images within the different fat compartmentsthat avoids the partial volume effects associated withtraditional fat segmentation methods. The method wastested on 18 subjects before and after a period of fastfoodhyper-alimentation showing high stability andperformance in all analysis steps.
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| 3. |
- Läthén, Gunnar, et al.
(författare)
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Phase Based Level Set Segmentation of Blood Vessels
- 2008
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Ingår i: Proceedings of 19th International Conference on Pattern Recognition. - : IEEE Computer Society. - 9781424421756 - 9781424421749 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- The segmentation and analysis of blood vessels hasreceived much attention in the research community. Theresults aid numerous applications for diagnosis andtreatment of vascular diseases. Here we use level setpropagation with local phase information to capture theboundaries of vessels. The basic notion is that localphase, extracted using quadrature filters, allows us todistinguish between lines and edges in an image. Notingthat vessels appear either as lines or edge pairs, weintegrate multiple scales and capture information aboutvessels of varying width. The outcome is a “global”phase which can be used to drive a contour robustly towardsthe vessel edges. We show promising results in2D and 3D. Comparison with a related method givessimilar or even better results and at a computationalcost several orders of magnitude less. Even with verysparse initializations, our method captures a large portionof the vessel tree.
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| 4. |
- Nordberg, Klas, 1963-
(författare)
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Efficient Triangulation Based on 3D Euclidean Optimization
- 2008
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Ingår i: International Conference on Pattern Recognition (ICPR). - : IEEE. - 9781424421749 - 9781424421756 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- This paper presents a method for triangulation of 3D points given their projections in two images. Recent results show that the triangulation mapping can be represented as a linear operator K applied to the outer product of corresponding homogeneous image coordinates, leading to a triangulation of very low computational complexity. K can be determined from the camera matrices, together with a so-called blind plane, but we show here that it can be further refined by a process similar to Gold Standard methods for camera matrix estimation. In particular it is demonstrated that K can be adjusted to minimize the Euclidean L, residual 3D error, bringing it down to the same level as the optimal triangulation by Hartley and Sturm. The resulting K optimally fits a set of 2D+2D+3D data where the error is measured in the 3D space. Assuming that this calibration set is representative for a particular application, where later only the 2D points are known, this K can be used for triangulation of 3D points in an optimal way, which in addition is very efficient since the optimization need only be made once for the point set. The refinement of K is made by iteratively reducing errors in the 3D and 2D domains, respectively. Experiments on real data suggests that very few iterations are needed to accomplish useful results.
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| 5. |
- Viksten, Fredrik, 1976-, et al.
(författare)
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Point-of-Interest Detection for Range Data
- 2008
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Ingår i: International Conference on Pattern Recognition (ICPR). - : IEEE. - 9781424421756 - 9781424421749 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- Point-of-interest detection is a way of reducing the amount of data that needs to be processed in a certain application and is widely used in 2D image analysis. In 2D image analysis, point-of-interest detection is usually related to extraction of local descriptors for object recognition, classification, registration or pose estimation. In analysis of range data however, some local descriptors have been published in the last decade or so, but most of them do not mention any kind of point-of-interest detection. We here show how to use an extended Harris detector on range data and discuss variants of the Harris measure. All described variants of the Harris detector for 3D should also be usable in medical image analysis, but we focus on the range data case. We do present a performance evaluation of the described variants of the Harris detector on range data.
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| 6. |
- Assabie, Yaregal, 1975-, et al.
(författare)
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Lexicon-based Offline Recognition of Amharic Words in Unconstrained Handwritten Text
- 2008
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Ingår i: 19th International Conference on Pattern Recognition. - New York : IEEE Computer Society. - 9781424421749
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Konferensbidrag (refereegranskat)abstract
- This paper describes an offline handwriting recognition system for Amharic words based on lexicon. The system computes direction fields of scanned handwritten documents, from which pseudo-characters are segmented. The pseudo-characters are organized based on their proximity and direction to form text lines. Words are then segmented by analyzing the relative gap between subsequent pseudocharacters in text lines. For each segmented word image, the structural characteristics of pseudo-characters are syntactically analyzed to predict a set of plausible characters forming the word. The most likelihood word is finally selected among candidates by matching against the lexicon. The system is tested by a database of unconstrained handwritten Amharic documents collected from various sources. The lexicon is prepared from words appearing in the collected database.
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| 7. |
- Dahl, Ola, et al.
(författare)
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Dynamic Structure and Motion Estimation based on Non-linear Adaptive Observers
- 2008
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Ingår i: 2008 19th International Conference on Pattern Recognition. - 9781424421749
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Konferensbidrag (refereegranskat)abstract
- Structure and motion estimation from long image sequences is a an important and difficult problem in computer vision. We propose a novel approach based on nonlinear and adaptive observers based on a dynamic model of the motion. The estimation of the threedimensional position and velocity of the camera as well as the three-dimensional structure of the scene is done by observing states and parameters of a nonlinear dynamic system, containing a perspective transformation in the output equation, often referred to as a perspective dynamic system. An advantage of the proposed method is that it is filter-based, i.e. it provides an estimate of structure and motion at each time instance, which is then updated based on a novel image in the sequence. The observer demonstrates a trade-off compared to a more computer vision oriented approach, where no specific assumptions regarding the motion dynamics are required, but instead additional feature points are needed. Finally, the performance of the proposed method is shown in simulated experiments.
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| 8. |
- Fundana, Ketut, et al.
(författare)
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Continuous Graph Cut Segmentation with Shape Priors
- 2008
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Ingår i: 2008 19th International Conference on Pattern Recognition. - 9781424421749
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Konferensbidrag (refereegranskat)abstract
- In this paper we propose a novel prior-based variational object segmentation method in a global minimization framework which unifies image segmentation and image denoising. The idea of the proposed method is to convexify the energy functional of the Chan-Vese method in order to find a global minimizer, so called continuous graph cuts. The method is extended by adding an additional shape constraint into the convex energy functional in order to segment an object using prior information. We show that the energy functional including a shape prior term can be relaxed from optimization over characteristic functions to optimization over arbitrary functions followed by a thresholding at an arbitrarily chosen level between 0 and 1. Experimental results demonstrate the performance and robustness of the method to segment objects in real images.
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| 9. |
- Karlsson, Johan, et al.
(författare)
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MDL Patch Correspondences on Unlabeled Images with Occlusions
- 2008
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Ingår i: 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops). - 9781424423392 ; , s. 999-1006, s. 3249-3253
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Konferensbidrag (refereegranskat)abstract
- Automatic construction of Shape and Appearance Models from examples via establishing correspondences across the training set has been successful in the last decades. One successful measure for establishing correspondences of high quality is minimum description length (MDL). In other approaches it has been shown that parts+geometry models which model the appearance of parts of the object and the geometric relation between the parts have been successful for automatic model building. In this paper it is shown how to fuse the above approaches and use MDL to fully automatically build optimal parts+geometry models from unlabeled images.
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| 10. |
- Maboudi Afkham, Heydar, et al.
(författare)
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Joint Visual Vocabulary For Animal Classification
- 2008
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Ingår i: 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6. - 9781424421749 ; , s. 2019-2022
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Konferensbidrag (refereegranskat)abstract
- This paper presents a method for visual object categorization based on encoding the joint textural information in objects and the surrounding back-ground, and requiring no segmentation during recognition. The framework can be used together with various learning techniques and model representations. Here we use this framework with simple probabilistic models and more complex representations obtained using Support Vector Machines. We prove that our approach provides good recognition performance for complex problems for which some of the existing methods have difficulties. Additionally, we introduce a new extensive database containing realistic images of animals in complex natural environments. We asses the database in a set of experiments in which we compare the performance of our approach with a recently proposed method.
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