| 1. |
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| 2. |
- Boykov, Yuri, et al.
(författare)
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Guest Editorial: Energy Optimization Methods
- 2013
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Ingår i: International Journal of Computer Vision. - : Springer Science and Business Media LLC. - 1573-1405 .- 0920-5691. ; 104:3, s. 221-222
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 3. |
- Brissman, Emil, 1987-, et al.
(författare)
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Recurrent Graph Neural Networks for Video Instance Segmentation
- 2023
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Ingår i: International Journal of Computer Vision. - : Springer. - 0920-5691 .- 1573-1405. ; 131, s. 471-495
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Tidskriftsartikel (refereegranskat)abstract
- Video instance segmentation is one of the core problems in computer vision. Formulating a purely learning-based method, which models the generic track management required to solve the video instance segmentation task, is a highly challenging problem. In this work, we propose a novel learning framework where the entire video instance segmentation problem is modeled jointly. To this end, we design a graph neural network that in each frame jointly processes all detections and a memory of previously seen tracks. Past information is considered and processed via a recurrent connection. We demonstrate the effectiveness of the proposed approach in comprehensive experiments. Our approach operates online at over 25 FPS and obtains 16.3 AP on the challenging OVIS benchmark, setting a new state-of-the-art. We further conduct detailed ablative experiments that validate the different aspects of our approach. Code is available at https://github.com/emibr948/RGNNVIS-PlusPlus.
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| 4. |
- Broomé, Sara, et al.
(författare)
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Going Deeper than Tracking : A Survey of Computer-Vision Based Recognition of Animal Pain and Emotions
- 2023
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Ingår i: International Journal of Computer Vision. - : Springer Nature. - 0920-5691 .- 1573-1405. ; 131:2, s. 572-590
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Tidskriftsartikel (refereegranskat)abstract
- Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go ‘deeper’ than tracking, and address automated recognition of animals’ internal states such as emotions and pain with the aim of improving animal welfare, making this a timely moment for a systematization of the field. This paper provides a comprehensive survey of computer vision-based research on recognition of pain and emotional states in animals, addressing both facial and bodily behavior analysis. We summarize the efforts that have been presented so far within this topic—classifying them across different dimensions, highlight challenges and research gaps, and provide best practice recommendations for advancing the field, and some future directions for research.
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| 5. |
- Brunnström, Kjell, et al.
(författare)
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Active fixation for scene exploration
- 1996
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Ingår i: International Journal of Computer Vision. - : Kluwer Academic Publishers. - 0920-5691 .- 1573-1405. ; 17:2, s. 137-162
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Tidskriftsartikel (refereegranskat)abstract
- It is well-known that active selection of fixation points in humans is highly context and task dependent. It is therefore likely that successful computational processes for fixation in active vision should be so too. We are considering active fixation in the context of recognition of man-made objects characterized by their shapes. In this situation the qualitative shape and type of observed junctions play an important role. The fixations are driven by a grouping strategy, which forms sets of connected junctions separated from the surrounding at depth discontinuities. We have furthermore developed a methodology for rapid active detection and classification of junctions by selection of fixation points. The approach is based on direct computations from image data and allows integration of stereo and accommodation cues with luminance information. This work form a part of an effort to perform active recognition of generic objects, in the spirit of Malik and Biederman, but on real imagery rather than on line-drawings.
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| 6. |
- Byröd, Martin, et al.
(författare)
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Fast and Stable Polynomial Equation Solving and Its Application to Computer Vision
- 2009
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Ingår i: International Journal of Computer Vision. - : Springer Science and Business Media LLC. - 1573-1405 .- 0920-5691. ; 84:3, s. 237-256
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents several new results on techniques for solving systems of polynomial equations in computer vision. Gröbner basis techniques for equation solving have been applied successfully to several geometric computer vision problems. However, in many cases these methods are plagued by numerical problems. In this paper we derive a generalization of the Gröbner basis method for polynomial equation solving, which improves overall numerical stability. We show how the action matrix can be computed in the general setting of an arbitrary linear basis for ℂ[x]/I. In particular, two improvements on the stability of the computations are made by studying how the linear basis for ℂ[x]/I should be selected. The first of these strategies utilizes QR factorization with column pivoting and the second is based on singular value decomposition (SVD). Moreover, it is shown how to improve stability further by an adaptive scheme for truncation of the Gröbner basis. These new techniques are studied on some of the latest reported uses of Gröbner basis methods in computer vision and we demonstrate dramatically improved numerical stability making it possible to solve a larger class of problems than previously possible.
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| 7. |
- Demirci, M. Fatih, et al.
(författare)
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Object recognition as many-to-many feature matching
- 2006
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Ingår i: International Journal of Computer Vision. - : Springer Science and Business Media LLC. - 0920-5691 .- 1573-1405. ; 69:2, s. 203-222
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Tidskriftsartikel (refereegranskat)abstract
- Object recognition can be formulated as matching image features to model features. When recognition is exemplar-based, feature correspondence is one-to-one. However, segmentation errors, articulation, scale difference, and within-class deformation can yield image and model features which don't match one-to-one but rather many-to-many. Adopting a graph-based representation of a set of features, we present a matching algorithm that establishes many-to-many correspondences between the nodes of two noisy, vertex-labeled weighted graphs. Our approach reduces the problem of many-to-many matching of weighted graphs to that of many-to-many matching of weighted point sets in a normed vector space. This is accomplished by embedding the initial weighted graphs into a normed vector space with low distortion using a novel embedding technique based on a spherical encoding of graph structure. Many-to-many vector correspondences established by the Earth Mover's Distance framework are mapped back into many-to-many correspondences between graph nodes. Empirical evaluation of the algorithm on an extensive set of recognition trials, including a comparison with two competing graph matching approaches, demonstrates both the robustness and efficacy of the overall approach.
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| 8. |
- Duits, Remco, et al.
(författare)
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Image Analysis and Reconstruction using a Wavelet Transform Constructed from a Reducible Representation of the Euclidean Motion Group
- 2007
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Ingår i: International Journal of Computer Vision. - : Springer Science and Business Media LLC. - 0920-5691 .- 1573-1405. ; 72:1, s. 79-102
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Tidskriftsartikel (refereegranskat)abstract
- Inspired by the early visual system of many mammalians we consider the construction of-and reconstruction from- an orientation score Uf:R2×S1→C as a local orientation representation of an image, f:R2→R . The mapping f↦Uf is a wavelet transform Wψ corresponding to a reducible representation of the Euclidean motion group onto L2(R2) and oriented wavelet ψ∈L2(R2) . This wavelet transform is a special case of a recently developed generalization of the standard wavelet theory and has the practical advantage over the usual wavelet approaches in image analysis (constructed by irreducible representations of the similitude group) that it allows a stable reconstruction from one (single scale) orientation score. Since our wavelet transform is a unitary mapping with stable inverse, we directly relate operations on orientation scores to operations on images in a robust manner.Furthermore, by geometrical examination of the Euclidean motion group G=R2R×T , which is the domain of our orientation scores, we deduce that an operator Φ on orientation scores must be left invariant to ensure that the corresponding operator W−1ψΦWψ on images is Euclidean invariant. As an example we consider all linear second order left invariant evolutions on orientation scores corresponding to stochastic processes on G. As an application we detect elongated structures in (medical) images and automatically close the gaps between them.Finally, we consider robust orientation estimates by means of channel representations, where we combine robust orientation estimation and learning of wavelets resulting in an auto-associative processing of orientation features. Here linear averaging of the channel representation is equivalent to robust orientation estimation and an adaptation of the wavelet to the statistics of the considered image class leads to an auto-associative behavior of the system.
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| 9. |
- Ellis, Liam, et al.
(författare)
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Linear Regression and Adaptive Appearance Models for Fast Simultaneous Modelling and Tracking
- 2011
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Ingår i: International Journal of Computer Vision. - : Springer Verlag (Germany). - 0920-5691 .- 1573-1405. ; 95:2, s. 154-179
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Tidskriftsartikel (refereegranskat)abstract
- This work proposes an approach to tracking by regression that uses no hard-coded models and no offline learning stage. The Linear Predictor (LP) tracker has been shown to be highly computationally efficient, resulting in fast tracking. Regression tracking techniques tend to require offline learning to learn suitable regression functions. This work removes the need for offline learning and therefore increases the applicability of the technique. The online-LP tracker can simply be seeded with an initial target location, akin to the ubiquitous Lucas-Kanade algorithm that tracks by registering an image template via minimisation. A fundamental issue for all trackers is the representation of the target appearance and how this representation is able to adapt to changes in target appearance over time. The two proposed methods, LP-SMAT and LP-MED, demonstrate the ability to adapt to large appearance variations by incrementally building an appearance model that identifies modes or aspects of the target appearance and associates these aspects to the Linear Predictor trackers to which they are best suited. Experiments comparing and evaluating regression and registration techniques are presented along with performance evaluations favourably comparing the proposed tracker and appearance model learning methods to other state of the art simultaneous modelling and tracking approaches.
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| 10. |
- Enqvist, Olof, et al.
(författare)
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Tractable Algorithms for Robust Model Estimation
- 2015
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Ingår i: International Journal of Computer Vision. - : Springer Science and Business Media LLC. - 1573-1405 .- 0920-5691. ; 112:1, s. 115-129
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Tidskriftsartikel (refereegranskat)abstract
- What is the computational complexity of geometric model estimation in the presence of noise and outliers? We show that the number of outliers can be minimized in polynomial time with respect to the number of measurements, although exponential in the model dimension. Moreover, for a large class of problems, we prove that the statistically more desirable truncated L2-norm can be optimized with the same complexity. In a similar vein, it is also shown how to transform a multi-model estimation problem into a purely combinatorial one—with worst-case complexity that is polynomial in the number of measurements but exponential in the number of models. We apply our framework to a series of hard fitting problems. It gives a practical method for simultaneously dealing with measurement noise and large amounts of outliers in the estimation of low-dimensional models. Experimental results and a comparison to random sampling techniques are presented for the applications rigid registration, triangulation and stitching.
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