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Results 1 - 10
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2,129
Contour Detection and Hierarchical Image Segmentation
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2010
"... This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on spectral clustering. Our segmentati ..."
Abstract
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Cited by 389 (24 self)
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segmentation algorithm consists of generic machinery for transforming the output of any contour detector into a hierarchical region tree. In this manner, we reduce the problem of image segmentation to that of contour detection. Extensive experimental evaluation demonstrates that both our contour detection
Matching words and pictures
- JOURNAL OF MACHINE LEARNING RESEARCH
, 2003
"... We present a new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text. Learning the joint distribution of image regions and words has many applications. We consider in detail predicting words associated with whole images (auto-annotation ..."
Abstract
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Cited by 665 (40 self)
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We present a new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text. Learning the joint distribution of image regions and words has many applications. We consider in detail predicting words associated with whole images (auto
An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1993
"... A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices. Cl ..."
Abstract
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Cited by 360 (0 self)
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A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices
Semantic Texton Forests for Image Categorization and Segmentation
"... We propose semantic texton forests, efficient and powerful new low-level features. These are ensembles of decision trees that act directly on image pixels, and therefore do not need the expensive computation of filter-bank responses or local descriptors. They are extremely fast to both train and tes ..."
Abstract
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Cited by 304 (13 self)
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and test, especially compared with k-means clustering and nearest-neighbor assignment of feature descriptors. The nodes in the trees provide (i) an implicit hierarchical clustering into semantic textons, and (ii) an explicit local classification estimate. Our second contribution, the bag of semantic
Graph Cuts and Efficient N-D Image Segmentation
, 2006
"... 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: segmentation of objects in image data. Despite its simplicity, this application epitomizes the best features ..."
Abstract
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Cited by 307 (7 self)
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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: segmentation of objects in image data. Despite its simplicity, this application epitomizes the best features
Learning by Watching: Extracting Reusable Task Knowledge from Visual Observation of Human Performance
- IEEE Transactions on Robotics and Automation
, 1994
"... A novel task instruction method for future intelligent robots is presented. In our method, a robot learns reusable task plans by watching a human perform assembly tasks. Functional units and working algorithms for visual recognition and analysis of human action sequences are presented. The overall s ..."
Abstract
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Cited by 298 (6 self)
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system is model based and integrated at the symbolic level. Temporal segmentation of a continuous task performance into meaningful units and identification of each operation is processed in real time by concurrent recognition processes under active attention control. Dependency among assembly operations
Associative hierarchical CRFs for object class image segmentation
- in Proc. ICCV
, 2009
"... Most methods for object class segmentation are formulated as a labelling problem over a single choice of quantisation of an image space- pixels, segments or group of segments. It is well known that each quantisation has its fair share of pros and cons; and the existence of a common optimal quantisat ..."
Abstract
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Cited by 172 (25 self)
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Most methods for object class segmentation are formulated as a labelling problem over a single choice of quantisation of an image space- pixels, segments or group of segments. It is well known that each quantisation has its fair share of pros and cons; and the existence of a common optimal
Speaker, Environment And Channel Change Detection And Clustering Via The Bayesian Information Criterion
, 1998
"... In this paper, we are interested in detecting changes in speaker identity, environmental condition and channel condition; we call this the problem of acoustic change detection. The input audio stream can be modeled as a Gaussian process in the cepstral space. We present a maximum likelihood approach ..."
Abstract
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Cited by 272 (2 self)
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approach to detect turns of a Gaussian process; the decision of a turn is based on the Bayesian Information Criterion (BIC), a model selection criterion well-known in the statistics literature. The BIC criterion can also be applied as a termination criterion in hierarchical methods for clustering of audio
Incorporating Contextual Information in Recommender Systems Using a Multidimensional Approach
- ACM Transactions on Information Systems
, 2005
"... The paper presents a multidimensional (MD) approach to recommender systems that can provide recommendations based on additional contextual information besides the typical information on users and items used in most of the current recommender systems. This approach supports multiple dimensions, exten ..."
Abstract
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Cited by 236 (9 self)
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, extensive profiling, and hierarchical aggregation of recommendations. The paper also presents a multidimensional rating estimation method capable of selecting two-dimensional segments of ratings pertinent to the recommendation context and applying standard collaborative filtering or other traditional two
Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs
- In Conference on Information and Knowledge Management (CIKM
, 2008
"... Most analysis of web search relevance and performance takes a single query as the unit of search engine interaction. When studies attempt to group queries together by task or session, a timeout is typically used to identify the boundary. However, users query search engines in order to accomplish tas ..."
Abstract
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Cited by 147 (1 self)
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or addressed automatic identification of interleaved and hierarchically organized search tasks. We propose and evaluate a method for the automated segmentation of users’ query streams into hierarchical units. Our classifiers can improve on timeout segmentation, as well as other previously published approaches
Results 1 - 10
of
2,129
