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Author | Agata Lapedriza; David Masip; David Sanchez | ||||
Title | Emotions Classification using Facial Action Units Recognition | Type | Conference Article | ||
Year | 2014 | Publication | 17th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
Volume | 269 | Issue | Pages | 55-64 | |
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Abstract | In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection. | ||||
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ISSN | ISBN | 978-1-61499-451-0 | Medium | ||
Area | Expedition | Conference | CCIA | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ LMS2014 | Serial | 2622 | ||
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Author | Mariella Dimiccoli | ||||
Title | Figure-ground segregation: A fully nonlocal approach | Type | Journal Article | ||
Year | 2016 | Publication | Vision Research | Abbreviated Journal | VR |
Volume | 126 | Issue | Pages | 308-317 | |
Keywords | Figure-ground segregation; Nonlocal approach; Directional linear voting; Nonlinear diffusion | ||||
Abstract | We present a computational model that computes and integrates in a nonlocal fashion several configural cues for automatic figure-ground segregation. Our working hypothesis is that the figural status of each pixel is a nonlocal function of several geometric shape properties and it can be estimated without explicitly relying on object boundaries. The methodology is grounded on two elements: multi-directional linear voting and nonlinear diffusion. A first estimation of the figural status of each pixel is obtained as a result of a voting process, in which several differently oriented line-shaped neighborhoods vote to express their belief about the figural status of the pixel. A nonlinear diffusion process is then applied to enforce the coherence of figural status estimates among perceptually homogeneous regions. Computer simulations fit human perception and match the experimental evidence that several cues cooperate in defining figure-ground segregation. The results of this work suggest that figure-ground segregation involves feedback from cells with larger receptive fields in higher visual cortical areas. | ||||
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Notes | MILAB; | Approved | no | ||
Call Number | Admin @ si @ Dim2016b | Serial | 2623 | ||
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Author | Jorge Bernal; F. Javier Sanchez; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach | ||||
Title | Bulding up the future of colonoscopy: A synergy between clinicians and computer scientists | Type | Book Chapter | ||
Year | 2015 | Publication | Colonoscopy and Colorectal Cancer | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Intelligent systems; Image properties; Validation; Clinical drawbacks; Endoluminal scene description | ||||
Abstract | Recent advances in endoscopic technology have generated an increasing interest in strengthening the collaboration between clinicians and computers scientist to develop intelligent systems that can provide additional information to clinicians in the different stages of an intervention. The objective of this chapter is to identify clinical drawbacks of colonoscopy in order to define potential areas of collaboration. Once areas are defined, we present the challenges that colonoscopy images present in order computational methods to provide with meaningful output, including those related to image formation and acquisition, as they are proven to have an impact in the performance of an intelligent system. Finally, we also propose how to define validation frameworks in order to assess the performance of a given method, making an special emphasis on how databases should be created and annotated and which metrics should be used to evaluate systems correctly. | ||||
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ISSN | ISBN | 978-953-51-2225-8 | Medium | ||
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Notes | MV | Approved | no | ||
Call Number | Admin @ si @ BSR2015 | Serial | 2624 | ||
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Author | Youssef El Rhabi; Simon Loic; Brun Luc | ||||
Title | Estimation de la pose d’une caméra à partir d’un flux vidéo en s’approchant du temps réel | Type | Conference Article | ||
Year | 2015 | Publication | 15ème édition d'ORASIS, journées francophones des jeunes chercheurs en vision par ordinateur ORASIS2015 | Abbreviated Journal | |
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Keywords | Augmented Reality; SFM; SLAM; real time pose computation; 2D/3D registration | ||||
Abstract | Finding a way to estimate quickly and robustly the pose of an image is essential in augmented reality. Here we will discuss the approach we chose in order to get closer to real time by using SIFT points [4]. We propose a method based on filtering both SIFT points and images on which to focus on. Hence we will focus on relevant data. | ||||
Address | Amiens; France; June 2015 | ||||
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Area | Expedition | Conference | ORASIS | ||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RLL2015 | Serial | 2626 | ||
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Author | Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika | ||||
Title | Multi-observation Face Recognition in Videos based on Label Propagation | Type | Conference Article | ||
Year | 2015 | Publication | 6th Workshop on Analysis and Modeling of Faces and Gestures AMFG2015 | Abbreviated Journal | |
Volume | Issue | Pages | 10-17 | ||
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Abstract | In order to deal with the huge amount of content generated by social media, especially for indexing and retrieval purposes, the focus shifted from single object recognition to multi-observation object recognition. Of particular interest is the problem of face recognition (used as primary cue for persons’ identity assessment), since it is highly required by popular social media search engines like Facebook and Youtube. Recently, several approaches for graph-based label propagation were proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot cope properly with the rapid and frequent changes in data appearance, a phenomenon intrinsically related with video sequences. In this paper, we
propose a novel approach for efficient and adaptive graph construction, based on a two-phase scheme: (i) the first phase is used to adaptively find the neighbors of a sample and also to find the adequate weights for the minimization function of the second phase; (ii) in the second phase, the selected neighbors along with their corresponding weights are used to locally and collaboratively estimate the sparse affinity matrix weights. Experimental results performed on Honda Video Database (HVDB) and a subset of video sequences extracted from the popular TV-series ’Friends’ show a distinct advantage of the proposed method over the existing standard graph construction methods. |
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Address | Boston; USA; June 2015 | ||||
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Area | Expedition | Conference | CVPRW | ||
Notes | LAMP; 600.068; 600.072; | Approved | no | ||
Call Number | Admin @ si @ RBD2015 | Serial | 2627 | ||
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Author | Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez; Xavier Roca | ||||
Title | A coarse-to-fine approach for fast deformable object detection | Type | Journal Article | ||
Year | 2015 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 48 | Issue | 5 | Pages | 1844-1853 |
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Abstract | We present a method that can dramatically accelerate object detection with part based models. The method is based on the observation that the cost of detection is likely to be dominated by the cost of matching each part to the image, and not by the cost of computing the optimal configuration of the parts as commonly assumed. Therefore accelerating detection requires minimizing the number of
part-to-image comparisons. To this end we propose a multiple-resolutions hierarchical part based model and a corresponding coarse-to-fine inference procedure that recursively eliminates from the search space unpromising part placements. The method yields a ten-fold speedup over the standard dynamic programming approach and is complementary to the cascade-of-parts approach of [9]. Compared to the latter, our method does not have parameters to be determined empirically, which simplifies its use during the training of the model. Most importantly, the two techniques can be combined to obtain a very significant speedup, of two orders of magnitude in some cases. We evaluate our method extensively on the PASCAL VOC and INRIA datasets, demonstrating a very high increase in the detection speed with little degradation of the accuracy. |
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Notes | ISE; 600.078; 602.005; 605.001; 302.012 | Approved | no | ||
Call Number | Admin @ si @ PVG2015 | Serial | 2628 | ||
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Author | M. Cruz; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Ricardo Toledo; Angel Sappa | ||||
Title | Cross-spectral image registration and fusion: an evaluation study | Type | Conference Article | ||
Year | 2015 | Publication | 2nd International Conference on Machine Vision and Machine Learning | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | multispectral imaging; image registration; data fusion; infrared and visible spectra | ||||
Abstract | This paper presents a preliminary study on the registration and fusion of cross-spectral imaging. The objective is to evaluate the validity of widely used computer vision approaches when they are applied at different
spectral bands. In particular, we are interested in merging images from the infrared (both long wave infrared: LWIR and near infrared: NIR) and visible spectrum (VS). Experimental results with different data sets are presented. |
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Address | Barcelona; July 2015 | ||||
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Area | Expedition | Conference | MVML | ||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ CAV2015 | Serial | 2629 | ||
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Author | Cristhian A. Aguilera-Carrasco; Angel Sappa; Ricardo Toledo | ||||
Title | LGHD: a Feature Descriptor for Matching Across Non-Linear Intensity Variations | Type | Conference Article | ||
Year | 2015 | Publication | 22th IEEE International Conference on Image Processing | Abbreviated Journal | |
Volume | Issue | Pages | 178 - 181 | ||
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Address | Quebec; Canada; September 2015 | ||||
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Area | Expedition | Conference | ICIP | ||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ AST2015 | Serial | 2630 | ||
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Author | Xavier Otazu; Olivier Penacchio; Xim Cerda-Company | ||||
Title | Brightness and colour induction through contextual influences in V1 | Type | Conference Article | ||
Year | 2015 | Publication | Scottish Vision Group 2015 SGV2015 | Abbreviated Journal | |
Volume | 12 | Issue | 9 | Pages | 1208-2012 |
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Address | Carnoustie; Scotland; March 2015 | ||||
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Area | Expedition | Conference | SGV | ||
Notes | NEUROBIT; | Approved | no | ||
Call Number | Admin @ si @ OPC2015a | Serial | 2632 | ||
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Author | Olivier Penacchio; Xavier Otazu; A. wilkins; J. Harris | ||||
Title | Uncomfortable images prevent lateral interactions in the cortex from providing a sparse code | Type | Conference Article | ||
Year | 2015 | Publication | European Conference on Visual Perception ECVP2015 | Abbreviated Journal | |
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Address | Liverpool; uk; August 2015 | ||||
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Area | Expedition | Conference | ECVP | ||
Notes | NEUROBIT; | Approved | no | ||
Call Number | Admin @ si @ POW2015 | Serial | 2633 | ||
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Author | Xavier Otazu; Olivier Penacchio; Xim Cerda-Company | ||||
Title | An excitatory-inhibitory firing rate model accounts for brightness induction, colour induction and visual discomfort | Type | Conference Article | ||
Year | 2015 | Publication | Barcelona Computational, Cognitive and Systems Neuroscience | Abbreviated Journal | |
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Address | Barcelona; June 2015 | ||||
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Area | Expedition | Conference | BARCCSYN | ||
Notes | NEUROBIT; | Approved | no | ||
Call Number | Admin @ si @ OPC2015b | Serial | 2634 | ||
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Author | Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria | ||||
Title | Motility bar: a new tool for motility analysis of endoluminal videos | Type | Journal Article | ||
Year | 2015 | Publication | Computers in Biology and Medicine | Abbreviated Journal | CBM |
Volume | 65 | Issue | Pages | 320-330 | |
Keywords | Small intestine; Motility; WCE; Computer vision; Image classification | ||||
Abstract | Wireless Capsule Endoscopy (WCE) provides a new perspective of the small intestine, since it enables, for the first time, visualization of the entire organ. However, the long visual video analysis time, due to the large number of data in a single WCE study, was an important factor impeding the widespread use of the capsule as a tool for intestinal abnormalities detection. Therefore, the introduction of WCE triggered a new field for the application of computational methods, and in particular, of computer vision. In this paper, we follow the computational approach and come up with a new perspective on the small intestine motility problem. Our approach consists of three steps: first, we review a tool for the visualization of the motility information contained in WCE video; second, we propose algorithms for the characterization of two motility building-blocks: contraction detector and lumen size estimation; finally, we introduce an approach to detect segments of stable motility behavior. Our claims are supported by an evaluation performed with 10 WCE videos, suggesting that our methods ably capture the intestinal motility information. | ||||
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Notes | MILAB;MV | Approved | no | ||
Call Number | Admin @ si @ DSR2015 | Serial | 2635 | ||
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Author | Santiago Segui; Oriol Pujol; Jordi Vitria | ||||
Title | Learning to count with deep object features | Type | Conference Article | ||
Year | 2015 | Publication | Deep Vision: Deep Learning in Computer Vision, CVPR 2015 Workshop | Abbreviated Journal | |
Volume | Issue | Pages | 90-96 | ||
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Abstract | Learning to count is a learning strategy that has been recently proposed in the literature for dealing with problems where estimating the number of object instances in a scene is the final objective. In this framework, the task of learning to detect and localize individual object instances is seen as a harder task that can be evaded by casting the problem as that of computing a regression value from hand-crafted image features. In this paper we explore the features that are learned when training a counting convolutional neural
network in order to understand their underlying representation. To this end we define a counting problem for MNIST data and show that the internal representation of the network is able to classify digits in spite of the fact that no direct supervision was provided for them during training. We also present preliminary results about a deep network that is able to count the number of pedestrians in a scene. |
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Address | Boston; USA; June 2015 | ||||
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Area | Expedition | Conference | CVPRW | ||
Notes | MILAB; HuPBA; OR;MV | Approved | no | ||
Call Number | Admin @ si @ SPV2015 | Serial | 2636 | ||
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Author | Marc Bolaños; Maite Garolera; Petia Radeva | ||||
Title | Active labeling application applied to food-related object recognition | Type | Conference Article | ||
Year | 2013 | Publication | 5th International Workshop on Multimedia for Cooking & Eating Activities | Abbreviated Journal | |
Volume | Issue | Pages | 45-50 | ||
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Abstract | Every day, lifelogging devices, available for recording different aspects of our daily life, increase in number, quality and functions, just like the multiple applications that we give to them. Applying wearable devices to analyse the nutritional habits of people is a challenging application based on acquiring and analyzing life records in long periods of time. However, to extract the information of interest related to the eating patterns of people, we need automatic methods to process large amount of life-logging data (e.g. recognition of food-related objects). Creating a rich set of manually labeled samples to train the algorithms is slow, tedious and subjective. To address this problem, we propose a novel method in the framework of Active Labeling for construct- ing a training set of thousands of images. Inspired by the hierarchical sampling method for active learning [6], we propose an Active forest that organizes hierarchically the data for easy and fast labeling. Moreover, introducing a classifier into the hierarchical structures, as well as transforming the feature space for better data clustering, additionally im- prove the algorithm. Our method is successfully tested to label 89.700 food-related objects and achieves significant reduction in expert time labelling.
Active labeling application applied to food-related object recognition ResearchGate. Available from: http://www.researchgate.net/publication/262252017Activelabelingapplicationappliedtofood-relatedobjectrecognition [accessed Jul 14, 2015]. |
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Address | Barcelona; October 2013 | ||||
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Area | Expedition | Conference | ACM-CEA | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ BGR2013b | Serial | 2637 | ||
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Author | Marc Bolaños; R. Mestre; Estefania Talavera; Xavier Giro; Petia Radeva | ||||
Title | Visual Summary of Egocentric Photostreams by Representative Keyframes | Type | Conference Article | ||
Year | 2015 | Publication | IEEE International Conference on Multimedia and Expo ICMEW2015 | Abbreviated Journal | |
Volume | Issue | Pages | 1-6 | ||
Keywords | egocentric; lifelogging; summarization; keyframes | ||||
Abstract | Building a visual summary from an egocentric photostream captured by a lifelogging wearable camera is of high interest for different applications (e.g. memory reinforcement). In this paper, we propose a new summarization method based on keyframes selection that uses visual features extracted bymeans of a convolutional neural network. Our method applies an unsupervised clustering for dividing the photostreams into events, and finally extracts the most relevant keyframe for each event. We assess the results by applying a blind-taste test on a group of 20 people who assessed the quality of the
summaries. |
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Address | Torino; italy; July 2015 | ||||
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Series Volume | Series Issue | 978-1-4799-7079-7 | Edition | ||
ISSN | ISBN | 978-1-4799-7079-7 | Medium | ||
Area | Expedition | Conference | ICME | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ BMT2015 | Serial | 2638 | ||
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