| 1. |
- Eriksson, Anders P, et al.
(författare)
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On the bijectivity of thin-plate splines
- 2012
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Ingår i: Analysis for Science, Engineering and Beyond, The Tribute Workshop in Honour of Gunnar Sparr held in Lund, May 8-9, 2008. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642202360 - 9783642202353 ; 6, s. 93-141
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The thin-plate spline (TPS) has been widely used in a number of areas such as image warping, shape analysis and scattered data interpolation. Introduced by Bookstein (IEEE Trans. Pattern Anal. Mach. Intell. 11(6):567–585 1989), it is a natural interpolating function in two dimensions, parameterized by a finite number of landmarks. However, even though the thin-plate spline has a very intuitive interpretation as well as an elegant mathematical formulation, it has no inherent restriction to prevent folding, i.e. a non-bijective interpolating function. In this chapter we discuss some of the properties of the set of parameterizations that form bijective thin-plate splines, such as convexity and boundness. Methods for finding sufficient as well as necessary conditions for bijectivity are also presented. The methods are used in two settings (a) to register two images using thin-plate spline deformations, while ensuring bijectivity and (b) group-wise registration of a set of images, while enforcing bijectivity constraints.
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| 2. |
- Karlsson, Johan, et al.
(författare)
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Shape Modeling by Optimising Description Length Using Gradients and Parameterisation Invariance
- 2012
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Ingår i: Analysis for Science, Engineering and Beyond, The Tribute Workshop in Honour of Gunnar Sparr held in Lund, May 8-9, 2008. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642202353 - 9783642202360 ; 6, s. 51-91
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- In Statistical Shape Modeling, a dense correspondence between the shapes in the training set must be established. Traditionally this has been done by hand, a process that commonly requires a lot of work and is difficult, especially in 3D. In recent years there has been a lot of work on automatic construction of Shape Models. In recent papers (Davies et al., Medical Image Computing and Computer-Assisted Intervention MICCAI’2001, pp. 57–65, 2001; Davies et al., IEEE Trans. Med. Imaging. 21(5):525–537 2002; Kotcheff and Taylor, Med. Image Anal. 2:303–314 1998) Minimum Description Length, (MDL), is used to locate a dense correspondence between shapes. In this paper the gradient of the description length is derived. Using the gradient, MDL is optimised using steepest descent. The optimisation is therefore faster and experiments show that the resulting models are better. To characterise shape properties that are invariant to similarity transformations, it is first necessary to normalise with respect to the similarity transformations. This is normally done using Procrustes analysis. In this paper we propose to align shapes using the MDL criterion. The MDL based algorithm is compared to Procrustes on a number of data sets. It is concluded that there is improvement in generalisation when using MDL to align the shapes. In this paper novel theory to prevent the commonly occurring problem of clustering under correspondence optimisation is also presented. The problem is solved by calculating the covariance matrix of the shapes using a scalar product that is invariant to mutual reparameterisations. An algorithm for implementing the ideas is proposed and compared to Thodberg’s state of the art algorithm for automatic shape modeling. The suggested algorithm is more stable and the resulting models are of higher quality according to the generalisation measure and according to visual inspection of the specificity.
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| 3. |
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| 4. |
- Nilsson, Mikael, et al.
(författare)
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Learning Based Image Segmentation of Pigs in a Pen
- 2014
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Ingår i: ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- As farms are getting bigger with more animals, less manual supervision and attention can be given the animals on both group and individual level. In order not to jeopardize animal welfare, automated supervision is in some way already in use. Function and control of ventilation is already in use in modern pig stables, e.g. by the use of sensors for temperature, relative humidity and malfunction connected to alarm. However, by measuring continuously directly on the pigs, more information and more possibilities to adjust production inputs would be possible. In this work, the focus is on a key image processing algorithm aiding such a continuous system - segmentation of pigs in images from video. The proposed solution utilizes extended state-of-the-art features in combination with a structured prediction framework based on a logistic regression solver using elastic net regularization. Objective results on manually segmented images indicate that the proposed solution, based on learning, performs better than approaches suggested in recent publications addressing pig segmentation in video.
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| 5. |
- Lindström, Johan, et al.
(författare)
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Background and Foreground Modeling Using an Online EM Algorithm
- 2006
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Ingår i: IEEE International Workshop on Visual Surveillance. ; VS2006, s. 9-16
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Konferensbidrag (refereegranskat)abstract
- A novel approach to background/foreground segmentation using an online EM algorithm is presented. The method models each layer as a Gaussian mixture, with local, per pixel, parameters for the background layer and global parameters for the foreground layer, utilising information from the entire scene when estimating the foreground. Additionally, the online EM algorithm uses a progressive learning rate where the relative update speed of each Gaussian component depends on how often the component has been observed. It is shown that the progressive learning rate follows naturally from introduction of a forgetting factor in the log-likelihood. To reduce the number of mixture components similar foreground components are merged using a method based on the Kullback-Leibler distance. A bias is introduced in the variance estimates to avoid the known problem of singularities in the log-likelihood of Gaussian mixtures when the variance tends to zero. To allow a decoupling of the learning rate of the Gaussian components and the speed at which stationary objects are incorporated into the background a CUSUM detector is used instead of the prevailing method that uses the ratio of prior probability to standard deviation. The algorithm is scale invariant and its properties on gray-scale and RGB videos, as well as on output from an edge detector, is compared to that of another algorithm. Especially for the edge detector video performance increases dramatically.
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| 6. |
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| 7. |
- Nilsson, Mikael, et al.
(författare)
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Development of automatic surveillance of animal behaviour and welfare using image analysis and machine learned segmentation technique.
- 2015
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Ingår i: Animal. - 1751-7311 .- 1751-732X. ; 9:11, s. 1859-1865
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Tidskriftsartikel (refereegranskat)abstract
- In this paper the feasibility to extract the proportion of pigs located in different areas of a pig pen by advanced image analysis technique is explored and discussed for possible applications. For example, pigs generally locate themselves in the wet dunging area at high ambient temperatures in order to avoid heat stress, as wetting the body surface is the major path to dissipate the heat by evaporation. Thus, the portion of pigs in the dunging area and resting area, respectively, could be used as an indicator of failure of controlling the climate in the pig environment as pigs are not supposed to rest in the dunging area. The computer vision methodology utilizes a learning based segmentation approach using several features extracted from the image. The learning based approach applied is based on extended state-of-the-art features in combination with a structured prediction framework based on a logistic regression solver using elastic net regularization. In addition, the method is able to produce a probability per pixel rather than form a hard decision. This overcomes some of the limitations found in a setup using grey-scale information only. The pig pen is a difficult imaging environment because of challenging lighting conditions like shadows, poor lighting and poor contrast between pig and background. In order to test practical conditions, a pen containing nine young pigs was filmed from a top view perspective by an Axis M3006 camera with a resolution of 640×480 in three, 10-min sessions under different lighting conditions. The results indicate that a learning based method improves, in comparison with greyscale methods, the possibility to reliable identify proportions of pigs in different areas of the pen. Pigs with a changed behaviour (location) in the pen may indicate changed climate conditions. Changed individual behaviour may also indicate inferior health or acute illness.
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| 8. |
- Oskarsson, Magnus, et al.
(författare)
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Visual Tracking of Box Jellyfish: A Real-Time Motion Tracking System
- 2015
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Ingår i: Computer Vision and Pattern Recognition in Environmental Informatics. - : IGI Global. - 9781466694354 - 9781466694361 ; , s. 107-122
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Bokkapitel (refereegranskat)abstract
- In this chapter a system for tracking the motion of box jellyfish Tripedalia cystophora in a special test setup is investigated. The goal is to measure the motor response of the animal given certain visual stimuli. The approach is based on tracking the special sensory structures - the rhopalia - of the box jellyfish from high-speed video sequences. The focus has been on a real-time system with simple building blocks in the system. However, using a combination of simple intensity based detection and model based tracking promising tracking results with up to 95% accuracy are achieved.
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| 9. |
- Aanaes, H, et al.
(författare)
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Robust factorization
- 2002
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Ingår i: IEEE Transactions on Pattern Analysis and Machine Intelligence. - 1939-3539. ; 24:9, s. 1215-1225
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Tidskriftsartikel (refereegranskat)abstract
- Factorization algorithms for recovering structure and motion from an image stream have many advantages, but they usually require a set of well-tracked features. Such a set is in generally not available in practical applications. There is thus a need for making factorization algorithms deal effectively with errors in the tracked features. We propose a new and computationally efficient algorithm for applying an arbitrary errorfunction in the factorization scheme. This algorithm enables the use of robust statistical techniques and arbitrary noise models for the individual features. These techniques and models enable the factorization scheme to deal effectively with mismatched features, missing features, and noise on the individual features. The proposed approach further includes a new method for Euclidean reconstruction that significantly improves convergence of the factorization algorithms. The proposed algorithm has been implemented as a modification of the Christy-Horaud factorization scheme, which yields a perspective reconstruction. Based on this implementation, a considerable increase in error tolerance is demonstrated on real and synthetic data. The proposed scheme can, however, be applied to most other factorization algorithms.
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| 10. |
- Ahrnbom, Martin, et al.
(författare)
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Fast Classification of Empty and Occupied Parking Spaces Using Integral Channel Features
- 2016
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Ingår i: Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016. - 9781467388504 ; , s. 1609-1615
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Konferensbidrag (refereegranskat)abstract
- In this paper we present a novel, fast and accurate system for detecting the presence of cars in parking lots. The system is based on fast integral channel features and machine learning. The methods are well suited for running embedded on low performance platforms. The methods are tested on a database of nearly 700,000 images of parking spaces, where 48.5% are occupied and the rest are free. The experimental evaluation shows improved robustness in comparison to the baseline methods for the dataset.
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