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Author |
Partha Pratim Roy; Josep Llados; Umapada Pal |
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Title |
A Complete System for Detection and Recognition of Text in Graphical Documents using Background Information |
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Conference Article |
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Year |
2009 |
Publication |
5th International Conference on Computer Vision Theory and Applications |
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Lisboa, Portugal |
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978-989-8111-69-2 |
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VISAPP |
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DAG |
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no |
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Call Number |
DAG @ dag @ RLP2009 |
Serial |
1238 |
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Permanent link to this record |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Seal detection and recognition: An approach for document indexing |
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Conference Article |
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Year |
2009 |
Publication |
10th International Conference on Document Analysis and Recognition |
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Pages |
101–105 |
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Reliable indexing of documents having seal instances can be achieved by recognizing seal information. This paper presents a novel approach for detecting and classifying such multi-oriented seals in these documents. First, Hough Transform based methods are applied to extract the seal regions in documents. Next, isolated text characters within these regions are detected. Rotation and size invariant features and a support vector machine based classifier have been used to recognize these detected text characters. Next, for each pair of character, we encode their relative spatial organization using their distance and angular position with respect to the centre of the seal, and enter this code into a hash table. Given an input seal, we recognize the individual text characters and compute the code for pair-wise character based on the relative spatial organization. The code obtained from the input seal helps to retrieve model hypothesis from the hash table. The seal model to which we get maximum hypothesis is selected for the recognition of the input seal. The methodology is tested to index seal in rotation and size invariant environment and we obtained encouraging results. |
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Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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ICDAR |
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DAG |
Approved |
no |
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Call Number |
DAG @ dag @ RPL2009b |
Serial |
1239 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados; Mathieu Nicolas Delalandre |
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Title |
Multi-Oriented and Multi-Sized Touching Character Segmentation using Dynamic Programming |
Type |
Conference Article |
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Year |
2009 |
Publication |
10th International Conference on Document Analysis and Recognition |
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Pages |
11–15 |
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In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region at the background portion. Using Convex Hull information, we use these background information to find some initial points to segment a touching string into possible primitive segments (a primitive segment consists of a single character or a part of a character). Next these primitive segments are merged to get optimum segmentation and dynamic programming is applied using total likelihood of characters as the objective function. SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment, we obtained encouraging results. |
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Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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ICDAR |
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DAG |
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no |
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Call Number |
DAG @ dag @ RPL2009a |
Serial |
1240 |
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Author |
Carlo Gatta; Petia Radeva |
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Title |
Bilateral Enhancers |
Type |
Conference Article |
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Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
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Pages |
3161-3165 |
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Ten years ago the concept of bilateral filtering (BF) became popular in the image processing community. The core of the idea is to blend the effect of a spatial filter, as e.g. the Gaussian filter, with the effect of a filter that acts on image values. The two filters acts on orthogonal domains of a picture: the 2D lattice of the image support and the intensity (or color) domain. The BF approach is an intuitive way to blend these two filters giving rise to algorithms that perform difficult tasks requiring a relatively simple design. In this paper we extend the concept of BF, proposing the bilateral enhancers (BE). We show how to design proper functions to obtain an edge-preserving smoothing and a selective sharpening. Moreover, we show that the proposed algorithm can perform edge-preserving smoothing and selective sharpening simultaneously in a single filtering. |
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Cairo, Egypt |
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ISSN |
1522-4880 |
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978-1-4244-5653-6 |
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ICIP |
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Notes |
MILAB |
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no |
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Call Number |
BCNPCL @ bcnpcl @ GaR2009b |
Serial |
1243 |
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Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
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Title |
Efficient Object Pixel-Level Categorization using Bag of Features: Advances in Visual Computing |
Type |
Conference Article |
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Year |
2009 |
Publication |
5th International Symposium on Visual Computing |
Abbreviated Journal |
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Volume |
5875 |
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Pages |
44–55 |
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Abstract |
In this paper we present a pixel-level object categorization method suitable to be applied under real-time constraints. Since pixels are categorized using a bag of features scheme, the major bottleneck of such an approach would be the feature pooling in local histograms of visual words. Therefore, we propose to bypass this time-consuming step and directly obtain the score from a linear Support Vector Machine classifier. This is achieved by creating an integral image of the components of the SVM which can readily obtain the classification score for any image sub-window with only 10 additions and 2 products, regardless of its size. Besides, we evaluated the performance of two efficient feature quantization methods: the Hierarchical K-Means and the Extremely Randomized Forest. All experiments have been done in the Graz02 database, showing comparable, or even better results to related work with a lower computational cost. |
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Las Vegas, USA |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-10330-8 |
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ISVC |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ ATR2009a |
Serial |
1246 |
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Permanent link to this record |
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Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
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Title |
Visual Registration Method For A Low Cost Robot: Computer Vision Systems |
Type |
Conference Article |
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Year |
2009 |
Publication |
7th International Conference on Computer Vision Systems |
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Volume |
5815 |
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Pages |
204–214 |
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Abstract |
An autonomous mobile robot must face the correspondence or data association problem in order to carry out tasks like place recognition or unknown environment mapping. In order to put into correspondence two maps, most methods estimate the transformation relating the maps from matches established between low level feature extracted from sensor data. However, finding explicit matches between features is a challenging and computationally expensive task. In this paper, we propose a new method to align obstacle maps without searching explicit matches between features. The maps are obtained from a stereo pair. Then, we use a vocabulary tree approach to identify putative corresponding maps followed by the Newton minimization algorithm to find the transformation that relates both maps. The proposed method is evaluated in a typical office environment showing good performance. |
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Address |
Belgica |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-04666-7 |
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Conference |
ICVS |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ ATR2009b |
Serial |
1247 |
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Permanent link to this record |
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Author |
Arnau Ramisa; Shrihari Vasudevan; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras |
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Title |
Evaluation of the SIFT Object Recognition Method in Mobile Robots: Frontiers in Artificial Intelligence and Applications |
Type |
Conference Article |
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Year |
2009 |
Publication |
12th International Conference of the Catalan Association for Artificial Intelligence |
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Volume |
202 |
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Pages |
9-18 |
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General object recognition in mobile robots is of primary importance in order to enhance the representation of the environment that robots will use for their reasoning processes. Therefore, we contribute reduce this gap by evaluating the SIFT Object Recognition method in a challenging dataset, focusing on issues relevant to mobile robotics. Resistance of the method to the robotics working conditions was found, but it was limited mainly to well-textured objects. |
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Cardona, Spain |
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ISSN |
0922-6389 |
ISBN |
978-1-60750-061-2 |
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Conference |
CCIA |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RVA2009 |
Serial |
1248 |
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Permanent link to this record |
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Author |
Oscar Camara; Estanislao Oubel; Gemma Piella; Simone Balocco; Mathieu De Craene; Alejandro F. Frangi |
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Title |
Multi-sequence Registration of Cine, Tagged and Delay-Enhancement MRI with Shift Correction and Steerable Pyramid-Based Detagging |
Type |
Conference Article |
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Year |
2009 |
Publication |
5th International Conference on Functional Imaging and Modeling of the Heart |
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Volume |
5528 |
Issue |
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Pages |
330–338 |
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Abstract |
In this work, we present a registration framework for cardiac cine MRI (cMRI), tagged (tMRI) and delay-enhancement MRI (deMRI), where the two main issues to find an accurate alignment between these images have been taking into account: the presence of tags in tMRI and respiration artifacts in all sequences. A steerable pyramid image decomposition has been used for detagging purposes since it is suitable to extract high-order oriented structures by directional adaptive filtering. Shift correction of cMRI is achieved by firstly maximizing the similarity between the Long Axis and Short Axis cMRI. Subsequently, these shift-corrected images are used as target images in a rigid registration procedure with their corresponding tMRI/deMRI in order to correct their shift. The proposed registration framework has been evaluated by 840 registration tests, considerably improving the alignment of the MR images (mean RMS error of 2.04mm vs. 5.44mm). |
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Nice, France |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-01931-9 |
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FIMH |
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Notes |
MILAB |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ COP2009 |
Serial |
1255 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Simultaneous 3D face pose and person-specific shape estimation from a single image using a holistic approach |
Type |
Conference Article |
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Year |
2009 |
Publication |
IEEE Workshop on Applications of Computer Vision |
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This paper presents a new approach for the simultaneous estimation of the 3D pose and specific shape of a previously unseen face from a single image. The face pose is not limited to a frontal view. We describe a holistic approach based on a deformable 3D model and a learned statistical facial texture model. Rather than obtaining a person-specific facial surface, the goal of this work is to compute person-specific 3D face shape in terms of a few control parameters that are used by many applications. The proposed holistic approach estimates the 3D pose parameters as well as the face shape control parameters by registering the warped texture to a statistical face texture, which is carried out by a stochastic and genetic optimizer. The proposed approach has several features that make it very attractive: (i) it uses a single grey-scale image, (ii) it is person-independent, (iii) it is featureless (no facial feature extraction is required), and (iv) its learning stage is easy. The proposed approach lends itself nicely to 3D face tracking and face gesture recognition in monocular videos. We describe extensive experiments that show the feasibility and robustness of the proposed approach. |
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Utah, USA |
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ISSN |
1550-5790 |
ISBN |
978-1-4244-5497-6 |
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Conference |
WACV |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ DoR2009b |
Serial |
1256 |
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Author |
Bogdan Raducanu; Fadi Dornaika |
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Title |
Natural Facial Expression Recognition Using Dynamic and Static Schemes |
Type |
Conference Article |
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Year |
2009 |
Publication |
5th International Symposium on Visual Computing |
Abbreviated Journal |
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Volume |
5875 |
Issue |
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Pages |
730–739 |
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Abstract |
Affective computing is at the core of a new paradigm in HCI and AI represented by human-centered computing. Within this paradigm, it is expected that machines will be enabled with perceiving capabilities, making them aware about users’ affective state. The current paper addresses the problem of facial expression recognition from monocular videos sequences. We propose a dynamic facial expression recognition scheme, which is proven to be very efficient. Furthermore, it is conveniently compared with several static-based systems adopting different magnitude of facial expression. We provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). We also provide performance evaluations using arbitrary test video sequences. |
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Address |
Las Vegas, USA |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
ISBN |
978-3-642-10330-8 |
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ISVC |
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Notes |
OR;MV |
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no |
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Call Number |
BCNPCL @ bcnpcl @ RaD2009 |
Serial |
1257 |
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Author |
Anjan Dutta; Zeynep Akata |
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Title |
Semantically Tied Paired Cycle Consistency for Zero-Shot Sketch-based Image Retrieval |
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Conference Article |
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Year |
2019 |
Publication |
32nd IEEE Conference on Computer Vision and Pattern Recognition |
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Issue |
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Pages |
5089-5098 |
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Zero-shot sketch-based image retrieval (SBIR) is an emerging task in computer vision, allowing to retrieve natural images relevant to sketch queries that might not been seen in the training phase. Existing works either require aligned sketch-image pairs or inefficient memory fusion layer for mapping the visual information to a semantic space. In this work, we propose a semantically aligned paired cycle-consistent generative (SEM-PCYC) model for zero-shot SBIR, where each branch maps the visual information to a common semantic space via an adversarial training. Each of these branches maintains a cycle consistency that only requires supervision at category levels, and avoids the need of highly-priced aligned sketch-image pairs. A classification criteria on the generators' outputs ensures the visual to semantic space mapping to be discriminating. Furthermore, we propose to combine textual and hierarchical side information via a feature selection auto-encoder that selects discriminating side information within a same end-to-end model. Our results demonstrate a significant boost in zero-shot SBIR performance over the state-of-the-art on the challenging Sketchy and TU-Berlin datasets. |
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Long beach; California; USA; June 2019 |
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CVPR |
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DAG; 600.141; 600.121 |
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no |
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Call Number |
Admin @ si @ DuA2019 |
Serial |
3268 |
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Author |
Oriol Pujol; Eloi Puertas; Carlo Gatta |
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Title |
Multi-scale Stacked Sequential Learning |
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Conference Article |
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Year |
2009 |
Publication |
8th International Workshop of Multiple Classifier Systems |
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Volume |
5519 |
Issue |
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Pages |
262–271 |
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Abstract |
One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions. |
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Address |
Reykjavik, Iceland |
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Springer Berlin Heidelberg |
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0302-9743 |
ISBN |
978-3-642-02325-5 |
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MCS |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ PPG2009 |
Serial |
1260 |
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Permanent link to this record |
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Author |
Xavier Boix; Josep M. Gonfaus; Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Marco Pedersoli; Jordi Gonzalez; Joan Serrat |
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Title |
Combining local and global bag-of-word representations for semantic segmentation |
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Conference Article |
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Year |
2009 |
Publication |
Workshop on The PASCAL Visual Object Classes Challenge |
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Kyoto (Japan) |
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Area |
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Expedition |
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Conference |
ICCV |
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Notes |
ADAS;ISE |
Approved |
no |
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Call Number |
ADAS @ adas @ BGS2009 |
Serial |
1273 |
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Permanent link to this record |
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Author |
Mario Rojas; David Masip; A. Todorov; Jordi Vitria |
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Title |
Automatic Point-based Facial Trait Judgments Evaluation |
Type |
Conference Article |
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Year |
2010 |
Publication |
23rd IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
2715–2720 |
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Keywords |
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Abstract |
Humans constantly evaluate the personalities of other people using their faces. Facial trait judgments have been studied in the psychological field, and have been determined to influence important social outcomes of our lives, such as elections outcomes and social relationships. Recent work on textual descriptions of faces has shown that trait judgments are highly correlated. Further, behavioral studies suggest that two orthogonal dimensions, valence and dominance, can describe the basis of the human judgments from faces. In this paper, we used a corpus of behavioral data of judgments on different trait dimensions to automatically learn a trait predictor from facial pixel images. We study whether trait evaluations performed by humans can be learned using machine learning classifiers, and used later in automatic evaluations of new facial images. The experiments performed using local point-based descriptors show promising results in the evaluation of the main traits. |
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Address |
San Francisco CA, USA |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1063-6919 |
ISBN |
978-1-4244-6984-0 |
Medium |
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Area |
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Expedition |
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Conference |
CVPR |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ RMT2010 |
Serial |
1282 |
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Permanent link to this record |
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Author |
Santiago Segui; Laura Igual; Jordi Vitria |
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Title |
Weighted Bagging for Graph based One-Class Classifiers |
Type |
Conference Article |
|
Year |
2010 |
Publication |
9th International Workshop on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
5997 |
Issue |
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Pages |
1-10 |
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Keywords |
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Abstract |
Most conventional learning algorithms require both positive and negative training data for achieving accurate classification results. However, the problem of learning classifiers from only positive data arises in many applications where negative data are too costly, difficult to obtain, or not available at all. Minimum Spanning Tree Class Descriptor (MSTCD) was presented as a method that achieves better accuracies than other one-class classifiers in high dimensional data. However, the presence of outliers in the target class severely harms the performance of this classifier. In this paper we propose two bagging strategies for MSTCD that reduce the influence of outliers in training data. We show the improved performance on both real and artificially contaminated data. |
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Address |
Cairo, Egypt |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-12126-5 |
Medium |
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Area |
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Expedition |
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Conference |
MCS |
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Notes |
MILAB;OR;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ SIV2010 |
Serial |
1284 |
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Permanent link to this record |