Abstract. Combinatorial min-cut algorithms on graphs emerged as an increasingly useful tool for problems in vision. Typically, the use of graphcuts is motivated by one of the following two reasons....
Our work was inspired by recent advances in image segmentation where fluxbased functionals significantly improved alignment of object boundaries. We propose a novel photoflux functional for...
7. Active Concept Learning for Image Retrieval in Dynamic Databases (2008)
Maneesh Singh, Xiaofeng Ren, Yuri Boykov, Jing Zhong, Shuicheng Yan, Mingjing Li, ...
Nebojsa Jojic, Brendan Frey, Anitha Kannan. Pages 34–41. See the CD-ROM for a video of epitome learning and the epitome webpage for further examples, comparisons and software.
Our work was inspired by recent advances in image segmentation where fluxbased functionals significantly improved alignment of object boundaries. We propose a novel photoflux functional for...
Abstract. Combinatorial min-cut algorithms on graphs emerged as an increasingly useful tool for problems in vision. Typically, the use of graphcuts is motivated by one of the following two reasons....
Global optimization for shape fitting (2007)
We propose a global optimization framework for 3D shape reconstruction from sparse noisy 3D measurements frequently encountered in range scanning, sparse featurebased stereo, and shape-from-X. In...
Global optimization for shape fitting (2007)
We propose a global optimization framework for 3D shape reconstruction from sparse noisy 3D measurements frequently encountered in range scanning, sparse featurebased stereo, and shape-from-X. In...
This paper adds a number of novel concepts into global s/t cut methods improving their efficiency and making them relevant for a wider class of applications in vision where algorithms should ideally...
Oriented Visibility for Multiview Reconstruction (2006)
Victor Lempitsky, Yuri Boykov, Denis Ivanov, D. Ivanov
Visibility estimation is arguably the most di#cult problem in dense 3D reconstruction from multiple arbitrary views. In this paper, we propose a simple new approach to estimating visibility based on...
Photoflux Maximizing Shapes (2006)
Our work was inspired by recent advances in image segmentation where flux based functionals significantly improved alignment of object boundaries. We propose a novel photoflux functional for...
An integral solution to surface evolution PDEs via geo-cuts (2006)
Yuri Boykov, Vladimir Kolmogorov, Daniel Cremers, Andrew Delong
Abstract. We introduce a new approach to modelling gradient flows of contours and surfaces. While standard variational methods (e.g. level sets) compute local interface motion in a differential...
An integral solution to surface evolution PDEs via geo-cuts (2006)
Yuri Boykov, Vladimir Kolmogorov, Daniel Cremers, Andrew Delong
Abstract. We introduce a new approach to modelling gradient flows of contours and surfaces. While standard variational methods (e.g. level sets) compute local interface motion in a differential...
An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision (2004)
Yuri Boykov, Vladimir Kolmogorov
Abstract. After [10, 15, 12, 2, 4] minimum cut/maximum ow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The...
An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision (2004)
Yuri Boykov, Vladimir Kolmogorov
After [15, 31, 19, 8, 25, 5] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The combinatorial...
An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision (2004)
Yuri Boykov, Vladimir Kolmogorov
Abstract. After [10, 15, 12, 2,4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The...
An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision (2004)
Yuri Boykov, Vladimir Kolmogorov
After [15, 31, 19, 8, 25, 5] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The combinatorial...
Computing geodesics and minimal surfaces via graph cuts (2003)
Geodesic active contours and graph cuts are two standard image segmentation techniques. We introduce a new segmentation method combining some of their benefits. Our main intuition is that any cut on...
Computing Geodesics and Minimal Surfaces via Graph Cuts (2003)
Yuri Boykov Imaging, Yuri Boykov
Geodesic active contours and graph cuts are two standard image segmentation techniques. We introduce a new segmentation method combining some of their benefits. Our main intuition is that any cut on...
DOI: 10.1007/s11263-006-7934-5 Graph Cuts and Efficient N-D Image Segmentation (2003)
Abstract. Combinatorial graph cut algorithms have been successfully applied to a wide range of problems in vision and graphics. This paper focusses on possibly the simplest application of graph-cuts:...
Fast approximate energy minimization via graph cuts (2001)
Yuri Boykov, Olga Veksler, Ramin Zabih
In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function’s smoothness term must only...
Fast approximate energy minimization via graph cuts (2001)
Yuri Boykov, Olga Veksler, Ramin Zabih
Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A common constraint is that the labels should vary smoothly almost everywhere while preserving sharp...
Fast approximate energy minimization via graph cuts (2001)
Yuri Boykov, Olga Veksler, Ramin Zabih
In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function’s smoothness term must only...
Fast approximate energy minimization via graph cuts (2001)
Yuri Boykov, Olga Veksler, Ramin Zabih
AbstractÐMany tasks in computer vision involve assigning a label (such as disparity) to every pixel. A common constraint is that the labels should vary smoothly almost everywhere while preserving...
Fast approximate energy minimization via graph cuts (2001)
Yuri Boykov, Olga Veksler, Ramin Zabih
In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function's smoothness term must only...
Fast approximate energy minimization via graph cuts (2001)
Yuri Boykov, Olga Veksler, Ramin Zabih
Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A common constraint is that the labels should vary smoothly almost everywhere while preserving sharp...
Fast approximate energy minimization via graph cuts (2001)
Yuri Boykov, Olga Veksler, Ramin Zabih
AbstractÐMany tasks in computer vision involve assigning a label (such as disparity) to every pixel. A common constraint is that the labels should vary smoothly almost everywhere while preserving...
Segmentation of dynamic N-D data sets via graph cuts using markov models (2001)
Yuri Boykov, Vivian S. Lee, Henry Rusinek, Ravi Bansal
Abstract. This paper describes a new segmentation technique for multidimensional dynamic data. One example of such data is a perfusion sequence where a number of 3D MRI volumes shows the dynamics of...
A Graph Based Algorithm for Bayesian Object Recognition (2000)
Boykov, Yuri, Huttenlocher, Daniel
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. Our approach assumes that both the location of the...
A Graph Based Algorithm for Bayesian Object Recognition (2000)
Boykov, Yuri, Huttenlocher, Daniel
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. Our approach assumes that both the location of the...
Interactive organ segmentation using graph cuts (2000)
Yuri Boykov, Marie-pierre Jolly
Abstract. An N-dimensional image is divided into “object ” and “background” segments using a graph cut approach. A graph is formed by connecting all pairs of neighboring image pixels (voxels)...
Adaptive Bayesian Recognition in Tracking Rigid Objects (2000)
Yuri Boykov, Daniel P. Huttenlocher
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we find a maximum a...
A Bayesian Framework for Model Based Tracking (1999)
Boykov, Yuri, Huttenlocher, Daniel
We present a Bayesian framework for tracking an object in a sequence of image frames. A maximum a posteriori (MAP) recognition method is used to detect the object in each image frame, and a Kalman...
A Bayesian Framework for Model Based Tracking (1999)
Boykov, Yuri, Huttenlocher, Daniel
We present a Bayesian framework for tracking an object in a sequence of image frames. A maximum a posteriori (MAP) recognition method is used to detect the object in each image frame, and a Kalman...
A new algorithm for energy minimization with discontinuities (1999)
Yuri Boykov, Olga Veksler, Ramin Zabih
Abstract. Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. These tasks can be formulated as energy minimization problems. In this paper, we consider a...
Fast Approximate Energy Minimization via Graph Cuts (1999)
Yuri Boykov, Olga Veksler, Ramin Zabih
Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A common constraint is that the labels should vary smoothly almost everywhere. These tasks are naturally...
Fast Approximate Energy Minimization via Graph Cuts (1999)
Yuri Boykov, Olga Veksler, Ramin Zabih
In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function 's smoothness term must only...
A New Algorithm for Energy Minimization with Discontinuities (1999)
Yuri Boykov, Olga Veksler, Ramin Zabih
. Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. These tasks can be formulated as energy minimization problems. In this paper, we consider a natural class...
A New Bayesian Framework for Object Recognition (1998)
Boykov, Yuri, Huttenlocher, Daniel
We describe a new approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. The main advantage of this approach is that it...
A New Bayesian Framework for Object Recognition (1998)
Boykov, Yuri, Huttenlocher, Daniel
We describe a new approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. The main advantage of this approach is that it...
Markov random fields with efficient approximations (1998)
Yuri Boykov, Olga Veksler, Ramin Zabih
Markov Random Fields (MRF’s) can be used for a wide variety of vision problems. In this paper we focus on MRF’s with two-valued clique potentials, which form a generalized Potts model. We show...
A variable window approach to early vision (1998)
Yuri Boykov, Olga Veksler, Student Member, Ramin Zabih
Abstract—Early vision relies heavily on rectangular windows for tasks such as smoothing and computing correspondence. While rectangular windows are efficient, they yield poor results near object...
Efficient restoration of multicolor image with independent noise (1998)
Yuri Boykov, Olga Veksler, Ramin Zabih
We consider the problem of maximum a posteriori (MAP) restoration of multicolor images where each pixel has been degraded by independent arbitrary noise. We assume that the prior distribution is...
A variable window approach to early vision (1998)
Yuri Boykov, Olga Veksler, Ramin Zabih
correspondence Early vision relies heavily on rectangular windows for tasks such as smoothing and computing correspondence. While rectangular windows are efficient, they yield poor results near...
Markov random fields with efficient approximations (1998)
Yuri Boykov, Olga Veksler, Ramin Zabih
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generalized Potts model. We...
A Variable Window Approach to Early Vision (1998)
Yuri Boykov, Olga Veksler, Ramin Zabih
Early vision relies heavily on rectangular windows for tasks such as smoothing and computing correspondence. While rectangular windows are e#cient, they yield poor results near object boundaries. We...
A New Bayesian Framework for Object Recognition (1998)
Yuri Boykov, Daniel Huttenlocher
We describe a new approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. The main advantage of this approach is that it...
Efficient Restoration of Multicolor Images with Independent Noise (1998)
Yuri Boykov, Olga Veksler, Ramin Zabih
We consider the problem of maximum a posteriori (MAP) restoration of multicolor images where each pixel has been degraded by independent arbitrary noise. We assume that the prior distribution is...
Markov random fields with efficient approximations (1998)
Yuri Boykov, Olga Veksler, Ramin Zabih
Markov Random Fields (MRF’s) can be used for a wide variety of vision problems. In this paper we focus on MRF’s with two-valued clique potentials, which form a generalized Potts model. We show...
Markov random fields with efficient approximations (1998)
Yuri Boykov, Olga Veksler, Ramin Zabih
Markov Random Fields (MRF’s) can be used for a wide variety of vision problems. In this paper we focus on MRF’s with two-valued clique potentials, which form a generalized Potts model. We show...
A Variable Window Approach to Early Vision (1997)
Boykov, Yuri, Veksler, Olga, Zabih, Ramin
Early vision relies heavily on rectangular windows for tasks such as smoothing and computing correspondence. While rectangular windows are efficient, they yield poor results near object boundaries....
Markov Random Fields with Efficient Approximations (1997)
Boykov, Yuri, Veksler, Olga, Zabih, Ramin
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we address the estimation of first-order MRF's with a particular clique potential that resembles a well....
A Variable Window Approach to Early Vision (1997)
Boykov, Yuri, Veksler, Olga, Zabih, Ramin
Early vision relies heavily on rectangular windows for tasks such as smoothing and computing correspondence. While rectangular windows are efficient, they yield poor results near object boundaries....
Markov Random Fields with Efficient Approximations (1997)
Boykov, Yuri, Veksler, Olga, Zabih, Ramin
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we address the estimation of first-order MRF's with a particular clique potential that resembles a well....
Disparity component matching for visual correspondence (1997)
Yuri Boykov, Olga Veksler, Ramin Zabih
We present a method for computing dense visual correspondence based on general assumptions about scene geometry. Our algorithm does not rely on correlation, and uses a variable region of support. We...
Disparity Component Matching for Visual Correspondence (1997)
Yuri Boykov, Olga Veksler, Ramin Zabih
We present a method for computing dense visual correspondence based on general assumptions about scene geometry. Our algorithm does not rely on correlation, and uses a variable region of support. We...
Disparity Component Matching for Visual Correspondence (1997)
Yuri Boykov, Olga Veksler, Ramin Zabih
We present a method for computing dense visual correspondence based on general assumptions about scene geometry. Our algorithm does not rely on correlation, and uses a variable region of support. We...
Disparity component matching for visual correspondence (1997)
Yuri Boykov, Olga Veksler, Ramin Zabih
We present a method for computing dense visual correspondence based on general assumptions about scene geometry. Our algorithm does not rely on correlation, and uses a variable region of support. We...
Energy Minimization with Discontinuities
Yuri Boykov, Olga Veksler, Ramin Zabih
Many tasks in computer vision can be formulated as energy minimization problems. In this paper, we consider a natural class of energy functions that permits discontinuities. We show that minimizing...