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Author | Pedro Herruzo; Marc Bolaños; Petia Radeva | ||||
Title | Can a CNN Recognize Catalan Diet? | Type | Book Chapter | ||
Year | 2016 | Publication | AIP Conference Proceedings | Abbreviated Journal | |
Volume | 1773 | Issue | Pages | ||
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Abstract | CoRR abs/1607.08811
Nowadays, we can find several diseases related to the unhealthy diet habits of the population, such as diabetes, obesity, anemia, bulimia and anorexia. In many cases, these diseases are related to the food consumption of people. Mediterranean diet is scientifically known as a healthy diet that helps to prevent many metabolic diseases. In particular, our work focuses on the recognition of Mediterranean food and dishes. The development of this methodology would allow to analise the daily habits of users with wearable cameras, within the topic of lifelogging. By using automatic mechanisms we could build an objective tool for the analysis of the patient’s behavior, allowing specialists to discover unhealthy food patterns and understand the user’s lifestyle. With the aim to automatically recognize a complete diet, we introduce a challenging multi-labeled dataset related to Mediter-ranean diet called FoodCAT. The first type of label provided consists of 115 food classes with an average of 400 images per dish, and the second one consists of 12 food categories with an average of 3800 pictures per class. This dataset will serve as a basis for the development of automatic diet recognition. In this context, deep learning and more specifically, Convolutional Neural Networks (CNNs), currently are state-of-the-art methods for automatic food recognition. In our work, we compare several architectures for image classification, with the purpose of diet recognition. Applying the best model for recognising food categories, we achieve a top-1 accuracy of 72.29%, and top-5 of 97.07%. In a complete diet recognition of dishes from Mediterranean diet, enlarged with the Food-101 dataset for international dishes recognition, we achieve a top-1 accuracy of 68.07%, and top-5 of 89.53%, for a total of 115+101 food classes. |
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ HBR2016 | Serial | 2837 | ||
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Author | Pejman Rasti; Tonis Uiboupin; Sergio Escalera; Gholamreza Anbarjafari | ||||
Title | Convolutional Neural Network Super Resolution for Face Recognition in Surveillance Monitoring | Type | Conference Article | ||
Year | 2016 | Publication | 9th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
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Address | Palma de Mallorca; Spain; July 2016 | ||||
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Area | Expedition | Conference | AMDO | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ RUE2016 | Serial | 2846 | ||
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Author | Dennis H. Lundtoft; Kamal Nasrollahi; Thomas B. Moeslund; Sergio Escalera | ||||
Title | Spatiotemporal Facial Super-Pixels for Pain Detection | Type | Conference Article | ||
Year | 2016 | Publication | 9th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Facial images; Super-pixels; Spatiotemporal filters; Pain detection | ||||
Abstract | Best student paper award.
Pain detection using facial images is of critical importance in many Health applications. Since pain is a spatiotemporal process, recent works on this topic employ facial spatiotemporal features to detect pain. These systems extract such features from the entire area of the face. In this paper, we show that by employing super-pixels we can divide the face into three regions, in a way that only one of these regions (about one third of the face) contributes to the pain estimation and the other two regions can be discarded. The experimental results on the UNBCMcMaster database show that the proposed system using this single region outperforms state-of-the-art systems in detecting no-pain scenarios, while it reaches comparable results in detecting weak and severe pain scenarios. |
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Address | Palma de Mallorca; Spain; July 2016 | ||||
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Area | Expedition | Conference | AMDO | ||
Notes | HUPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ LNM2016 | Serial | 2847 | ||
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Author | Mark Philip Philipsen; Anders Jorgensen; Thomas B. Moeslund; Sergio Escalera | ||||
Title | RGB-D Segmentation of Poultry Entrails | Type | Conference Article | ||
Year | 2016 | Publication | 9th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
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Abstract | Best commercial paper award. | ||||
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Area | Expedition | Conference | AMDO | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ PJM2016 | Serial | 2848 | ||
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Author | Antoni Gurgui; Debora Gil; Enric Marti; Vicente Grau | ||||
Title | Left-Ventricle Basal Region Constrained Parametric Mapping to Unitary Domain | Type | Conference Article | ||
Year | 2016 | Publication | 7th International Workshop on Statistical Atlases & Computational Modelling of the Heart | Abbreviated Journal | |
Volume | 10124 | Issue | Pages | 163-171 | |
Keywords | Laplacian; Constrained maps; Parameterization; Basal ring | ||||
Abstract | Due to its complex geometry, the basal ring is often omitted when putting different heart geometries into correspondence. In this paper, we present the first results on a new mapping of the left ventricle basal rings onto a normalized coordinate system using a fold-over free approach to the solution to the Laplacian. To guarantee correspondences between different basal rings, we imposed some internal constrained positions at anatomical landmarks in the normalized coordinate system. To prevent internal fold-overs, constraints are handled by cutting the volume into regions defined by anatomical features and mapping each piece of the volume separately. Initial results presented in this paper indicate that our method is able to handle internal constrains without introducing fold-overs and thus guarantees one-to-one mappings between different basal ring geometries. | ||||
Address | Athens; October 2016 | ||||
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Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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Area | Expedition | Conference | STACOM | ||
Notes | IAM; | Approved | no | ||
Call Number | Admin @ si @ GGM2016 | Serial | 2884 | ||
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Author | Muhammad Anwer Rao; Fahad Shahbaz Khan; Joost Van de Weijer; Jorma Laaksonen | ||||
Title | Combining Holistic and Part-based Deep Representations for Computational Painting Categorization | Type | Conference Article | ||
Year | 2016 | Publication | 6th International Conference on Multimedia Retrieval | Abbreviated Journal | |
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Abstract | Automatic analysis of visual art, such as paintings, is a challenging inter-disciplinary research problem. Conventional approaches only rely on global scene characteristics by encoding holistic information for computational painting categorization.We argue that such approaches are sub-optimal and that discriminative common visual structures provide complementary information for painting classification. We present an approach that encodes both the global scene layout and discriminative latent common structures for computational painting categorization. The region of interests are automatically extracted, without any manual part labeling, by training class-specific deformable part-based models. Both holistic and region-of-interests are then described using multi-scale dense convolutional features. These features are pooled separately using Fisher vector encoding and concatenated afterwards in a single image representation. Experiments are performed on a challenging dataset with 91 different painters and 13 diverse painting styles. Our approach outperforms the standard method, which only employs the global scene characteristics. Furthermore, our method achieves state-of-the-art results outperforming a recent multi-scale deep features based approach [11] by 6.4% and 3.8% respectively on artist and style classification. | ||||
Address | New York; USA; June 2016 | ||||
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Area | Expedition | Conference | ICMR | ||
Notes | LAMP; 600.068; 600.079;ADAS | Approved | no | ||
Call Number | Admin @ si @ RKW2016 | Serial | 2763 | ||
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Author | Aura Hernandez-Sabate; Lluis Albarracin; Daniel Calvo; Nuria Gorgorio | ||||
Title | EyeMath: Identifying Mathematics Problem Solving Processes in a RTS Video Game | Type | Conference Article | ||
Year | 2016 | Publication | 5th International Conference Games and Learning Alliance | Abbreviated Journal | |
Volume | 10056 | Issue | Pages | 50-59 | |
Keywords | Simulation environment; Automated Driving; Driver-Vehicle interaction | ||||
Abstract | Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical. | ||||
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Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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Area | Expedition | Conference | GALA | ||
Notes | ADAS;IAM; | Approved | no | ||
Call Number | HAC2016 | Serial | 2864 | ||
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Author | Jose Ramirez Moreno; Juan R Revilla; Miguel Reyes; Sergio Escalera | ||||
Title | Validación del Software ADIBAS asociado al sensor Kinect de Microsoft para la evaluación de la posición corporal | Type | Conference Article | ||
Year | 2016 | Publication | 4th Congreso WCPT-SAR | Abbreviated Journal | |
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Address | Buenos Aires; Argentina; June 2016 | ||||
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Area | Expedition | Conference | WCPT-SAR | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ RRR2016 | Serial | 2853 | ||
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Author | Fernando Vilariño; Dan Norton; Onur Ferhat | ||||
Title | The Eye Doesn't Click – Eyetracking and Digital Content Interaction | Type | Conference Article | ||
Year | 2016 | Publication | 4S/EASST Conference | Abbreviated Journal | |
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Address | Barcelona; Spain; September 2016 | ||||
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Area | Expedition | Conference | EASST | ||
Notes | MV; 600.097;SIAI | Approved | no | ||
Call Number | Admin @ si @VNF2016 | Serial | 2801 | ||
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Author | Jose A. Garcia; David Masip; Valerio Sbragaglia; Jacopo Aguzzi | ||||
Title | Using ORB, BoW and SVM to identificate and track tagged Norway lobster Nephrops Norvegicus (L.) | Type | Conference Article | ||
Year | 2016 | Publication | 3rd International Conference on Maritime Technology and Engineering | Abbreviated Journal | |
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Abstract | Sustainable capture policies of many species strongly depend on the understanding of their social behaviour. Nevertheless, the analysis of emergent behaviour in marine species poses several challenges. Usually animals are captured and observed in tanks, and their behaviour is inferred from their dynamics and interactions. Therefore, researchers must deal with thousands of hours of video data. Without loss of generality, this paper proposes a computer
vision approach to identify and track specific species, the Norway lobster, Nephrops norvegicus. We propose an identification scheme were animals are marked using black and white tags with a geometric shape in the center (holed triangle, filled triangle, holed circle and filled circle). Using a massive labelled dataset; we extract local features based on the ORB descriptor. These features are a posteriori clustered, and we construct a Bag of Visual Words feature vector per animal. This approximation yields us invariance to rotation and translation. A SVM classifier achieves generalization results above 99%. In a second contribution, we will make the code and training data publically available. |
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Address | Lisboa; Portugal; July 2016 | ||||
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Area | Expedition | Conference | MARTECH | ||
Notes | OR;MV; | Approved | no | ||
Call Number | Admin @ si @ GMS2016b | Serial | 2817 | ||
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Author | Carlos David Martinez Hinarejos; Josep Llados; Alicia Fornes; Francisco Casacuberta; Lluis de Las Heras; Joan Mas; Moises Pastor; Oriol Ramos Terrades; Joan Andreu Sanchez; Enrique Vidal; Fernando Vilariño | ||||
Title | Context, multimodality, and user collaboration in handwritten text processing: the CoMUN-HaT project | Type | Conference Article | ||
Year | 2016 | Publication | 3rd IberSPEECH | Abbreviated Journal | |
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Abstract | Processing of handwritten documents is a task that is of wide interest for many
purposes, such as those related to preserve cultural heritage. Handwritten text recognition techniques have been successfully applied during the last decade to obtain transcriptions of handwritten documents, and keyword spotting techniques have been applied for searching specific terms in image collections of handwritten documents. However, results on transcription and indexing are far from perfect. In this framework, the use of new data sources arises as a new paradigm that will allow for a better transcription and indexing of handwritten documents. Three main different data sources could be considered: context of the document (style, writer, historical time, topics,. . . ), multimodal data (representations of the document in a different modality, such as the speech signal of the dictation of the text), and user feedback (corrections, amendments,. . . ). The CoMUN-HaT project aims at the integration of these different data sources into the transcription and indexing task for handwritten documents: the use of context derived from the analysis of the documents, how multimodality can aid the recognition process to obtain more accurate transcriptions (including transcription in a modern version of the language), and integration into a userin-the-loop assisted text transcription framework. This will be reflected in the construction of a transcription and indexing platform that can be used by both professional and nonprofessional users, contributing to crowd-sourcing activities to preserve cultural heritage and to obtain an accessible version of the involved corpus. |
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Address | Lisboa; Portugal; November 2016 | ||||
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Area | Expedition | Conference | IberSPEECH | ||
Notes | DAG; MV; 600.097;SIAI | Approved | no | ||
Call Number | Admin @ si @MLF2016 | Serial | 2813 | ||
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Author | Yaxing Wang; L. Zhang; Joost Van de Weijer | ||||
Title | Ensembles of generative adversarial networks | Type | Conference Article | ||
Year | 2016 | Publication | 30th Annual Conference on Neural Information Processing Systems Worshops | Abbreviated Journal | |
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Abstract | Ensembles are a popular way to improve results of discriminative CNNs. The
combination of several networks trained starting from different initializations improves results significantly. In this paper we investigate the usage of ensembles of GANs. The specific nature of GANs opens up several new ways to construct ensembles. The first one is based on the fact that in the minimax game which is played to optimize the GAN objective the generator network keeps on changing even after the network can be considered optimal. As such ensembles of GANs can be constructed based on the same network initialization but just taking models which have different amount of iterations. These so-called self ensembles are much faster to train than traditional ensembles. The second method, called cascade GANs, redirects part of the training data which is badly modeled by the first GAN to another GAN. In experiments on the CIFAR10 dataset we show that ensembles of GANs obtain model probability distributions which better model the data distribution. In addition, we show that these improved results can be obtained at little additional computational cost. |
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Address | Barcelona; Spain; December 2016 | ||||
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Area | Expedition | Conference | NIPSW | ||
Notes | LAMP; 600.068 | Approved | no | ||
Call Number | Admin @ si @ WZW2016 | Serial | 2905 | ||
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Author | Guim Perarnau; Joost Van de Weijer; Bogdan Raducanu; Jose Manuel Alvarez | ||||
Title | Invertible conditional gans for image editing | Type | Conference Article | ||
Year | 2016 | Publication | 30th Annual Conference on Neural Information Processing Systems Worshops | Abbreviated Journal | |
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Abstract | Generative Adversarial Networks (GANs) have recently demonstrated to successfully approximate complex data distributions. A relevant extension of this model is conditional GANs (cGANs), where the introduction of external information allows to determine specific representations of the generated images. In this work, we evaluate encoders to inverse the mapping of a cGAN, i.e., mapping a real image into a latent space and a conditional representation. This allows, for example, to reconstruct and modify real images of faces conditioning on arbitrary attributes.
Additionally, we evaluate the design of cGANs. The combination of an encoder with a cGAN, which we call Invertible cGAN (IcGAN), enables to re-generate real images with deterministic complex modifications. |
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Address | Barcelona; Spain; December 2016 | ||||
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Area | Expedition | Conference | NIPSW | ||
Notes | LAMP; ADAS; 600.068 | Approved | no | ||
Call Number | Admin @ si @ PWR2016 | Serial | 2906 | ||
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Author | Xavier Baro; Sergio Escalera; Isabelle Guyon; Julio C. S. Jacques Junior; Lukasz Romaszko; Lisheng Sun; Sebastien Treguer; Evelyne Viegas | ||||
Title | Coompetitions in machine learning: case studies | Type | Conference Article | ||
Year | 2016 | Publication | 30th Annual Conference on Neural Information Processing Systems Worshops | Abbreviated Journal | |
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Address | Barcelona; Spain; December 2016 | ||||
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Area | Expedition | Conference | NIPSW | ||
Notes | HuPBA | Approved | no | ||
Call Number | Admin @ si @ BEG2016 | Serial | 2911 | ||
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Author | Jun Wan; Yibing Zhao; Shuai Zhou; Isabelle Guyon; Sergio Escalera | ||||
Title | ChaLearn Looking at People RGB-D Isolated and Continuous Datasets for Gesture Recognition | Type | Conference Article | ||
Year | 2016 | Publication | 29th IEEE Conference on Computer Vision and Pattern Recognition Worshops | Abbreviated Journal | |
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Abstract | In this paper, we present two large video multi-modal datasets for RGB and RGB-D gesture recognition: the ChaLearn LAP RGB-D Isolated Gesture Dataset (IsoGD)and the Continuous Gesture Dataset (ConGD). Both datasets are derived from the ChaLearn Gesture Dataset
(CGD) that has a total of more than 50000 gestures for the “one-shot-learning” competition. To increase the potential of the old dataset, we designed new well curated datasets composed of 249 gesture labels, and including 47933 gestures manually labeled the begin and end frames in sequences.Using these datasets we will open two competitions on the CodaLab platform so that researchers can test and compare their methods for “user independent” gesture recognition. The first challenge is designed for gesture spotting and recognition in continuous sequences of gestures while the second one is designed for gesture classification from segmented data. The baseline method based on the bag of visual words model is also presented. |
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Address | Las Vegas; USA; July 2016 | ||||
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Area | Expedition | Conference | CVPRW | ||
Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ WZZ2016 | Serial | 2771 | ||
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