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检索条件"机构=Pattern Analysis and Computer Vision"

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Fisher kernels for handwritten word-spotting

Fisher kernels for handwritten word-spotting

引用

ICDAR2009 - 10th International Conference on Document analysis and Recognition

作者： Perronnin, Florent Rodriguez-Serrano, Jose A. Textual and Visual Pattern Analysis Xerox Research Centre Europe France Computer Vision Centre Universitat Autonoma de Barcelona Spain

ISBN: (纸本)9780769537252

The Fisher kernel is a generic framework which combines the benefits of generative and discriminative approaches to pattern classification. In this contribution, we propose to apply this framework to handwritten word-spotting. Given a word image and a keyword generative model, the idea is to generate a vector which describes how the parameters of the keyword model should be modified to best fit the word image. This vector can then be used as the input of a discriminative classifier. We compare the performance of the proposed approach with that of a generative baseline on a challenging real-world dataset of customer letters. When the kernel used by the classifier is linear, the performance improvement is marginal but the proposed system is approximately 15 times faster than the baseline. If we use a non-linear kernel devised for this task, we obtain a 15% relative reduction of the error but the detector is approximately 15 times slower. © 2009 IEEE.

关键词： pattern recognition

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Kernel-based classification for brain connectivity graphs on the Riemannian manifold of positive definite matrices 12

Kernel-based classification for brain connectivity graphs on...

引用

12th IEEE International Symposium on Biomedical Imaging, ISBI 2015

作者： Dodero, Luca Minh, Ha Quang Biagio, Marco San Murino, Vittorio Sona, Diego Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy NeuroInformatics Laboratory Fondazione Bruno Kessler Trento Italy

ISBN: (纸本)9781479923748

An important task in connectomics studies is the classification of connectivity graphs coming from healthy and pathological subjects. In this paper, we propose a mathematical framework based on Riemannian geometry and kernel methods that can be applied to connectivity matrices for the classification task. We tested our approach using different real datasets of functional and structural connectivity, evaluating different metrics to describe the similarity between graphs. The empirical results obtained clearly show the superior performance of our approach compared with baseline methods, demonstrating the advantages of our manifold framework and its potential for other applications. © 2015 IEEE.

关键词： Geometry

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Multi-spectral scale and rotation invariant associative memory method for pattern recognition

Multi-spectral scale and rotation invariant associative memo...

引用

Optics, Illumination, and Image Sensing for Machine vision III 1988

作者： Kimball, Steven F. Messner, Richard A. University of New Hampshire Synthetic Vision and Pattern Analysis Laboratory Department of Electrical and Computer Engineering DurhamNH03824 United States

The method of using log-polar mapping with spectral band separation to form feature vectors for an associative memory is investigated. Log-polar mapping is used to provide the scale and rotation invariant properties. This reduces the teaching time and total capacity requirement for the associative memory because all orientations and sizes of the target object need not be learned. The images are also broken down into spatial frequency bands. The use of this technique is motivated by evidence that similar processes occur in the human visual system. Suspected benefits include enhanced recognition in the presence of noise and improved network robustness. Simulation results are presented for the case of character recognition. © 1989 SPIE. All rights reserved.

关键词： Associative processing

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A bag-of-pages approach to unordered multi-page document classification

A bag-of-pages approach to unordered multi-page document cla...

引用

International Conference on pattern Recognition

作者： Gordo, Albert Perronnin, Florent Computer Vision Center Universitat Autònoma de Barcelona Spain Textual and Visual Pattern Analysis Xerox Research Centre Europe France

ISBN: (纸本)9780769541099

We consider the problem of classifying documents containing multiple unordered pages. For this purpose, we propose a novel bag-of-pages document representation. To represent a document, one assigns every page to a prototype in a codebook of pages. This leads to a histogram representation which can then be fed to any discriminative classifier. We also consider several refinements over this initial approach. We show on two challenging datasets that the proposed approach significantly outperforms a baseline system. © 2010 IEEE.

关键词： Information retrieval systems

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Asymmetric distances for binary embeddings

Asymmetric distances for binary embeddings

引用

作者： Gordo, Albert Perronnin, Florent Computer Vision Center Universitat Autònoma de Barcelona Spain Textual and Visual Pattern Analysis Xerox Research Centre Europe France

ISBN: (纸本)9781457703942

In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH) and Semi-Supervised Hashing (SSH). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques. We also propose a novel simple binary embedding technique PCA Embedding (PCAE) which is shown to yield competitive results with respect to more complex algorithms such as SH and SSH. © 2011 IEEE.

关键词： Hamming distance

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Image analysis and Processing — ICIAP 2015 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Vittorio Murino Enrico Puppo

ISBN: (数字)9783319232348

ISBN: (纸本)9783319232331

The two-volume set LNCS 9279 and 9280 constitutes the refereed proceedings of the 18th International Conference on Image analysis and Processing, ICIAP 2015, held in Genoa, Italy, in September 2015. The 129 papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in the following seven topical sections: video analysis and understanding, multiview geometry and 3D computer vision, pattern recognition and machine learning, image analysis, detection and recognition, shape analysis and modeling, multimedia, and biomedical applications.

关键词： Image Processing and computer vision

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Guided Zoom: Questioning network evidence for fine-grained classification 30

Guided Zoom: Questioning network evidence for fine-grained c...

引用

30th British Machine vision Conference, BMVC 2019

作者： Bargal, Sarah Adel Zunino, Andrea Petsiuk, Vitali Zhang, Jianming Saenko, Kate Murino, Vittorio Sclaroff, Stan Department of Computer Science Boston University United States Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Italy Adobe Research Department of Computer Science University of Verona Italy

We propose Guided Zoom, an approach that utilizes spatial grounding of a model's decision to make more informed predictions. It does so by making sure the model has "the right reasons" for a prediction, defined as reasons that are coherent with those used to make similar correct decisions at training time. The reason/evidence upon which a deep convolutional neural network makes a prediction is defined to be the spatial grounding, in the pixel space, for a specific class conditional probability in the model output. Guided Zoom examines how reasonable such evidence is for each of the top-k predicted classes, rather than solely trusting the top-1 prediction. We show that Guided Zoom improves the classification accuracy of a deep convolutional neural network model and obtains state-of-the-art results on three fine-grained classification benchmark datasets. © 2019. The copyright of this document resides with its authors.

关键词： Forecasting

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Image analysis and Processing — ICIAP 2015 1

引用

丛书名： Lecture Notes in computer Science

1000年

作者： Vittorio Murino Enrico Puppo

ISBN: (数字)9783319232317

ISBN: (纸本)9783319232300

关键词： Image Processing and computer vision pattern Recognition Artificial Intelligence Algorithm analysis and Problem Complexity computer Graphics

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Statistical analysis of visual attentional patterns for video surveillance 1

引用

18th Iberoamerican Congress on pattern Recognition, CIARP 2013

作者： Roffo, Giorgio Cristani, Marco Pollick, Frank Segalin, Cristina Murino, Vittorio Department of Computer Science University of Verona Italy Pattern Analysis and Computer Vision Dept. Istituto Italiano di Tecnologia Italy School of Psychology University of Glasgow United Kingdom

ISBN: (数字)9783642418273

ISBN: (纸本)9783642418266

We show that the way people observe video sequences, other than what they observe, is important for the understanding and the prediction of human activities. In this study, we consider 36 surveillance videos, organized in four categories (confront, nothing, fight, play ): the videos are observed by 19 people, ten of them are experienced operators and the other nine are novices, and the gaze trajectories of both populations are recorded by an eye tracking device. Due to the proved superior ability of experienced operators in predicting violence in surveillance footage, our aim is to distinguish the two classes of people, highlighting in which respect expert operators differ from novices. Extracting spatio-temporal features from the eye tracking data, and training standard machine learning classifiers, we are able to discriminate the two groups of subjects with an average accuracy of 80.26%. The idea is that expert operators are more focused on few regions of the scene, sampling them with high frequency and low predictability. This can be thought as a first step toward the advanced automated analysis of video surveillance footage, where machines imitate as best as possible the attentive mechanisms of humans. © Springer-Verlag 2013.

关键词： Eye tracking

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Effective brain connectivity through a constrained autoregressive model 1

引用

1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2016

作者： Crimi, Alessandro Dodero, Luca Murino, Vittorio Sona, Diego Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genoa Italy Department of Computer Science University of Verona Verona Italy Neuroinformatics Laboratory Fondazione Bruno Kessler Trento Italy

ISBN: (数字)9783319467207

ISBN: (纸本)9783319467191

Integration of functional and structural brain connectivity is a topic receiving growing attention in the research community. Their fusion can,in fact,shed new light on brain functions. Targeting this issue,the manuscript proposes a constrained autoregressive model allowing to generate an "effective" connectivity matrix that model the structural connectivity integrating the functional activity. In practice,an initial structural connectivity representation is altered according to functional data,by minimizing the reconstruction error of an autoregressive model constrained by the structural prior. The proposed model has been tested in a community detection framework,where the brain is partitioned using the effective network across multiple subjects. Results showed that using the effective connectivity the resulting clusters better describe the functional interactions of different regions while maintaining the structural organization. © Springer International Publishing AG 2016.

关键词： Brain mapping

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