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| Author | Debora Gil; Petia Radeva; Fernando Vilariño | ||||
| Title | Anisotropic Contour Completion | Type | Conference Article | ||
| Year | 2003 | Publication | Proceedings of the IEEE International Conference on Image Processing | Abbreviated Journal | |
| Volume | Issue | Pages | I-869 | ||
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| Abstract | In this paper we introduce a novel application of the diffusion tensor for anisotropic image processing. The Anisotropic Contour Completion (ACC) we suggest consists in extending the characteristic function of the open curve by means of a degenerated diffusion tensor that prevents any diffusion in the normal direction. We show that ACC is equivalent to a dilation with a continuous elliptic structural element that takes into account the local orientation of the contours to be closed. Experiments on contours extracted from real images show that ACC produces shapes able to adapt to any curve in an active contour framework. 1. | ||||
| Address | Barcelona, Spain | ||||
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| Publisher | Place of Publication | Barcelona, Spain | Editor | ||
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| ISSN | ISBN | 0-7803-7751-6 | Medium | ||
| Area | Expedition | Conference  |
ICIP | ||
| Notes | IAM;MV;MILAB;SIAI | Approved | no | ||
| Call Number | IAM @ iam @ GRV2003 | Serial | 1539 | ||
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| Author | Andrei Polzounov; Artsiom Ablavatski; Sergio Escalera; Shijian Lu; Jianfei Cai | ||||
| Title | WordFences: Text Localization and Recognition | Type | Conference Article | ||
| Year | 2017 | Publication | 24th International Conference on Image Processing | Abbreviated Journal | |
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| Address | Beijing; China; September 2017 | ||||
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ICIP | ||
| Notes | HUPBA; no menciona | Approved | no | ||
| Call Number | Admin @ si @ PAE2017 | Serial | 3007 | ||
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| Author | Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva | ||||
| Title | All the people around me: face clustering in egocentric photo streams | Type | Conference Article | ||
| Year | 2017 | Publication | 24th International Conference on Image Processing | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | face discovery; face clustering; deepmatching; bag-of-tracklets; egocentric photo-streams | ||||
| Abstract | arxiv1703.01790
Given an unconstrained stream of images captured by a wearable photo-camera (2fpm), we propose an unsupervised bottom-up approach for automatic clustering appearing faces into the individual identities present in these data. The problem is challenging since images are acquired under real world conditions; hence the visible appearance of the people in the images undergoes intensive variations. Our proposed pipeline consists of first arranging the photo-stream into events, later, localizing the appearance of multiple people in them, and finally, grouping various appearances of the same person across different events. Experimental results performed on a dataset acquired by wearing a photo-camera during one month, demonstrate the effectiveness of the proposed approach for the considered purpose. |
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| Address | Beijing; China; September 2017 | ||||
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| Area | Expedition | Conference |
ICIP | ||
| Notes | MILAB; no menciona | Approved | no | ||
| Call Number | Admin @ si @ EDR2017 | Serial | 3025 | ||
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| Author | Xose M. Pardo; Petia Radeva; Juan J. Villanueva | ||||
| Title | Self-Training Statistic Snake for Image Segmentation and Tracking. | Type | Miscellaneous | ||
| Year | 1999 | Publication | Proceedings 10th International Conference on Image Analysis and Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 406-411 | ||
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| Abstract | . | ||||
| Address | Venice | ||||
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| Area | Expedition | Conference |
ICIAP | ||
| Notes | MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PRV1999 | Serial | 26 | ||
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| Author | J.R. Serra; J.B. Subirana | ||||
| Title | Adaptive non-cartesian networks for vision. | Type | Conference Article | ||
| Year | 1997 | Publication | Image Analysis and Processing. ICIAP 1997 | Abbreviated Journal | |
| Volume | 1311 | Issue | Pages | ||
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| Address | Florence | ||||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| Area | Expedition | Conference |
ICIAP | ||
| Notes | Approved | no | |||
| Call Number | Admin @ si @ SeS1997 | Serial | 212 | ||
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| Author | Patricia Suarez; Angel Sappa; Boris X. Vintimilla | ||||
| Title | Colorizing Infrared Images through a Triplet Conditional DCGAN Architecture | Type | Conference Article | ||
| Year | 2017 | Publication | 19th international conference on image analysis and processing | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | CNN in Multispectral Imaging; Image Colorization | ||||
| Abstract | This paper focuses on near infrared (NIR) image colorization by using a Conditional Deep Convolutional Generative Adversarial Network (CDCGAN) architecture model. The proposed architecture is based on the usage of a conditional probabilistic generative model. Firstly, it learns to colorize the given input image, by using a triplet model architecture that tackle every channel in an independent way. In the proposed model, the nal layer of red channel consider the infrared image to enhance the details, resulting in a sharp RGB image. Then, in the second stage, a discriminative model is used to estimate the probability that the generated image came from the training dataset, rather than the image automatically generated. Experimental results with a large set of real images are provided showing the validity of the proposed approach. Additionally, the proposed approach is compared with a state of the art approach showing better results. | ||||
| Address | Catania; Italy; September 2017 | ||||
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| Area | Expedition | Conference |
ICIAP | ||
| Notes | ADAS; MSIAU; 600.086; 600.122; 600.118 | Approved | no | ||
| Call Number | Admin @ si @ SSV2017c | Serial | 3016 | ||
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| Author | Alicia Fornes; Veronica Romero; Arnau Baro; Juan Ignacio Toledo; Joan Andreu Sanchez; Enrique Vidal; Josep Llados | ||||
| Title | ICDAR2017 Competition on Information Extraction in Historical Handwritten Records | Type | Conference Article | ||
| Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1389-1394 | ||
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| Abstract | The extraction of relevant information from historical handwritten document collections is one of the key steps in order to make these manuscripts available for access and searches. In this competition, the goal is to detect the named entities and assign each of them a semantic category, and therefore, to simulate the filling in of a knowledge database. This paper describes the dataset, the tasks, the evaluation metrics, the participants methods and the results. | ||||
| Address | Kyoto; Japan; November 2017 | ||||
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ICDAR | ||
| Notes | DAG; 600.097; 601.225; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ FRB2017 | Serial | 3052 | ||
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| Author | Pau Riba; Anjan Dutta; Josep Llados; Alicia Fornes; Sounak Dey | ||||
| Title | Improving Information Retrieval in Multiwriter Scenario by Exploiting the Similarity Graph of Document Terms | Type | Conference Article | ||
| Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 475-480 | ||
| Keywords | document terms; information retrieval; affinity graph; graph of document terms; multiwriter; graph diffusion | ||||
| Abstract | Information Retrieval (IR) is the activity of obtaining information resources relevant to a questioned information. It usually retrieves a set of objects ranked according to the relevancy to the needed fact. In document analysis, information retrieval receives a lot of attention in terms of symbol and word spotting. However, through decades the community mostly focused either on printed or on single writer scenario, where the
state-of-the-art results have achieved reasonable performance on the available datasets. Nevertheless, the existing algorithms do not perform accordingly on multiwriter scenario. A graph representing relations between a set of objects is a structure where each node delineates an individual element and the similarity between them is represented as a weight on the connecting edge. In this paper, we explore different analytics of graphs constructed from words or graphical symbols, such as diffusion, shortest path, etc. to improve the performance of information retrieval methods in multiwriter scenario |
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ICDAR | ||
| Notes | DAG; 600.097; 601.302; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ RDL2017a | Serial | 3053 | ||
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| Author | Anjan Dutta; Pau Riba; Josep Llados; Alicia Fornes | ||||
| Title | Pyramidal Stochastic Graphlet Embedding for Document Pattern Classification | Type | Conference Article | ||
| Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 33-38 | ||
| Keywords | graph embedding; hierarchical graph representation; graph clustering; stochastic graphlet embedding; graph classification | ||||
| Abstract | Document pattern classification methods using graphs have received a lot of attention because of its robust representation paradigm and rich theoretical background. However, the way of preserving and the process for delineating documents with graphs introduce noise in the rendition of underlying data, which creates instability in the graph representation. To deal with such unreliability in representation, in this paper, we propose Pyramidal Stochastic Graphlet Embedding (PSGE).
Given a graph representing a document pattern, our method first computes a graph pyramid by successively reducing the base graph. Once the graph pyramid is computed, we apply Stochastic Graphlet Embedding (SGE) for each level of the pyramid and combine their embedded representation to obtain a global delineation of the original graph. The consideration of pyramid of graphs rather than just a base graph extends the representational power of the graph embedding, which reduces the instability caused due to noise and distortion. When plugged with support vector machine, our proposed PSGE has outperformed the state-of-the-art results in recognition of handwritten words as well as graphical symbols |
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| Area | Expedition | Conference |
ICDAR | ||
| Notes | DAG; 600.097; 601.302; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ DRL2017 | Serial | 3054 | ||
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| Author | Juan Ignacio Toledo; Sounak Dey; Alicia Fornes; Josep Llados | ||||
| Title | Handwriting Recognition by Attribute embedding and Recurrent Neural Networks | Type | Conference Article | ||
| Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1038-1043 | ||
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| Abstract | Handwriting recognition consists in obtaining the transcription of a text image. Recent word spotting methods based on attribute embedding have shown good performance when recognizing words. However, they are holistic methods in the sense that they recognize the word as a whole (i.e. they find the closest word in the lexicon to the word image). Consequently,
these kinds of approaches are not able to deal with out of vocabulary words, which are common in historical manuscripts. Also, they cannot be extended to recognize text lines. In order to address these issues, in this paper we propose a handwriting recognition method that adapts the attribute embedding to sequence learning. Concretely, the method learns the attribute embedding of patches of word images with a convolutional neural network. Then, these embeddings are presented as a sequence to a recurrent neural network that produces the transcription. We obtain promising results even without the use of any kind of dictionary or language model |
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ICDAR | ||
| Notes | DAG; 600.097; 601.225; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ TDF2017 | Serial | 3055 | ||
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| Author | Sounak Dey; Anjan Dutta; Josep Llados; Alicia Fornes; Umapada Pal | ||||
| Title | Shallow Neural Network Model for Hand-drawn Symbol Recognition in Multi-Writer Scenario | Type | Conference Article | ||
| Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 31-32 | ||
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| Abstract | One of the main challenges in hand drawn symbol recognition is the variability among symbols because of the different writer styles. In this paper, we present and discuss some results recognizing hand-drawn symbols with a shallow neural network. A neural network model inspired from the LeNet architecture has been used to achieve state-of-the-art results with
very less training data, which is very unlikely to the data hungry deep neural network. From the results, it has become evident that the neural network architectures can efficiently describe and recognize hand drawn symbols from different writers and can model the inter author aberration |
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ICDAR | ||
| Notes | DAG; 600.097; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ DDL2017 | Serial | 3057 | ||
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| Author | Pau Riba; Anjan Dutta; Josep Llados; Alicia Fornes | ||||
| Title | Graph-based deep learning for graphics classification | Type | Conference Article | ||
| Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 29-30 | ||
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| Abstract | Graph-based representations are a common way to deal with graphics recognition problems. However, previous works were mainly focused on developing learning-free techniques. The success of deep learning frameworks have proved that learning is a powerful tool to solve many problems, however it is not straightforward to extend these methodologies to non euclidean data such as graphs. On the other hand, graphs are a good representational structure for graphical entities. In this work, we present some deep learning techniques that have been proposed in the literature for graph-based representations and
we show how they can be used in graphics recognition problems |
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ICDAR | ||
| Notes | DAG; 600.097; 601.302; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ RDL2017b | Serial | 3058 | ||
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| Author | Raul Gomez; Baoguang Shi; Lluis Gomez; Lukas Numann; Andreas Veit; Jiri Matas; Serge Belongie; Dimosthenis Karatzas | ||||
| Title | ICDAR2017 Robust Reading Challenge on COCO-Text | Type | Conference Article | ||
| Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
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| Address | Kyoto; Japan; November 2017 | ||||
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ICDAR | ||
| Notes | DAG; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ GSG2017 | Serial | 3076 | ||
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| Author | Juan Ramon Terven Salinas; Bogdan Raducanu; Maria Elena Meza-de-Luna; Joaquin Salas | ||||
| Title | Evaluating Real-Time Mirroring of Head Gestures using Smart Glasses | Type | Conference Article | ||
| Year | 2015 | Publication | 16th IEEE International Conference on Computer Vision Workshops | Abbreviated Journal | |
| Volume | Issue | Pages | 452-460 | ||
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| Abstract | Mirroring occurs when one person tends to mimic the non-verbal communication of their counterparts. Even though mirroring is a complex phenomenon, in this study, we focus on the detection of head-nodding as a simple non-verbal communication cue due to its significance as a gesture displayed during social interactions. This paper introduces a computer vision-based method to detect mirroring through the analysis of head gestures using wearable cameras (smart glasses). In addition, we study how such a method can be used to explore perceived competence. The proposed method has been evaluated and the experiments demonstrate how static and wearable cameras seem to be equally effective to gather the information required for the analysis. | ||||
| Address | Santiago de Chile; December 2015 | ||||
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ICCVW | ||
| Notes | LAMP; 600.068; 600.072; | Approved | no | ||
| Call Number | Admin @ si @ TRM2015 | Serial | 2722 | ||
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| Author | Jun Wan; Sergio Escalera; Gholamreza Anbarjafari; Hugo Jair Escalante; Xavier Baro; Isabelle Guyon; Meysam Madadi; Juri Allik; Jelena Gorbova; Chi Lin; Yiliang Xie | ||||
| Title | Results and Analysis of ChaLearn LAP Multi-modal Isolated and ContinuousGesture Recognition, and Real versus Fake Expressed Emotions Challenges | Type | Conference Article | ||
| Year | 2017 | Publication | Chalearn Workshop on Action, Gesture, and Emotion Recognition: Large Scale Multimodal Gesture Recognition and Real versus Fake expressed emotions at ICCV | Abbreviated Journal | |
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| Abstract | We analyze the results of the 2017 ChaLearn Looking at People Challenge at ICCV. The challenge comprised three tracks: (1) large-scale isolated (2) continuous gesture recognition, and (3) real versus fake expressed emotions tracks. It is the second round for both gesture recognition challenges, which were held first in the context of the ICPR 2016 workshop on “multimedia challenges beyond visual analysis”. In this second round, more participants joined the competitions, and the performances considerably improved compared to the first round. Particularly, the best recognition accuracy of isolated gesture recognition has improved from 56.90% to 67.71% in the IsoGD test set, and Mean Jaccard Index (MJI) of continuous gesture recognition has improved from 0.2869 to 0.6103 in the ConGD test set. The third track is the first challenge on real versus fake expressed emotion classification, including six emotion categories, for which a novel database was introduced. The first place was shared between two teams who achieved 67.70% averaged recognition rate on the test set. The data of the three tracks, the participants' code and method descriptions are publicly available to allow researchers to keep making progress in the field. | ||||
| Address | Venice; Italy; October 2017 | ||||
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ICCVW | ||
| Notes | HUPBA; no menciona | Approved | no | ||
| Call Number | Admin @ si @ WEA2017 | Serial | 3066 | ||
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