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| Author | Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva | ||||
| Title | Multi-Face Tracking by Extended Bag-of-Tracklets in Egocentric Videos | Type | Miscellaneous | ||
| Year | 2015 | Publication | Arxiv | Abbreviated Journal | |
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| Abstract | Egocentric images offer a hands-free way to record daily experiences and special events, where social interactions are of special interest. A natural question that arises is how to extract and track the appearance of multiple persons in a social event captured by a wearable camera. In this paper, we propose a novel method to find correspondences of multiple-faces in low temporal resolution egocentric sequences acquired through a wearable camera. This kind of sequences imposes additional challenges to the multitracking problem with respect to conventional videos. Due to the free motion of the camera and to its low temporal resolution (2 fpm), abrupt changes in the field of view, in illumination conditions and in the target location are very frequent. To overcome such a difficulty, we propose to generate, for each detected face, a set of correspondences along the whole sequence that we call tracklet and to take advantage of their redundancy to deal with both false positive face detections and unreliable tracklets. Similar tracklets are grouped into the so called extended bag-of-tracklets (eBoT), which are aimed to correspond to specific persons. Finally, a prototype tracklet is extracted for each eBoT. We validated our method over a dataset of 18.000 images from 38 egocentric sequences with 52 trackable persons and compared to the state-of-the-art methods, demonstrating its effectiveness and robustness. | ||||
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| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ ADR2015b | Serial | 2713 | ||
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| Author | Mariella Dimiccoli; Marc Bolaños; Estefania Talavera; Maedeh Aghaei; Stavri G. Nikolov; Petia Radeva | ||||
| Title | SR-Clustering: Semantic Regularized Clustering for Egocentric Photo Streams Segmentation | Type | Journal Article | ||
| Year | 2017 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
| Volume | 155 | Issue | Pages | 55-69 | |
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| Abstract | While wearable cameras are becoming increasingly popular, locating relevant information in large unstructured collections of egocentric images is still a tedious and time consuming processes. This paper addresses the problem of organizing egocentric photo streams acquired by a wearable camera into semantically meaningful segments. First, contextual and semantic information is extracted for each image by employing a Convolutional Neural Networks approach. Later, by integrating language processing, a vocabulary of concepts is defined in a semantic space. Finally, by exploiting the temporal coherence in photo streams, images which share contextual and semantic attributes are grouped together. The resulting temporal segmentation is particularly suited for further analysis, ranging from activity and event recognition to semantic indexing and summarization. Experiments over egocentric sets of nearly 17,000 images, show that the proposed approach outperforms state-of-the-art methods. | ||||
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| Notes | MILAB; 601.235 | Approved | no | ||
| Call Number | Admin @ si @ DBT2017 | Serial | 2714 | ||
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| Author | Suman Ghosh; Ernest Valveny | ||||
| Title | Query by String word spotting based on character bi-gram indexing | Type | Conference Article | ||
| Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 881-885 | ||
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| Abstract | In this paper we propose a segmentation-free query by string word spotting method. Both the documents and query strings are encoded using a recently proposed word representa- tion that projects images and strings into a common atribute space based on a pyramidal histogram of characters(PHOC). These attribute models are learned using linear SVMs over the Fisher Vector representation of the images along with the PHOC labels of the corresponding strings. In order to search through the whole page, document regions are indexed per character bi- gram using a similar attribute representation. On top of that, we propose an integral image representation of the document using a simplified version of the attribute model for efficient computation. Finally we introduce a re-ranking step in order to boost retrieval performance. We show state-of-the-art results for segmentation-free query by string word spotting in single-writer and multi-writer standard datasets | ||||
| Address | Nancy; France; August 2015 | ||||
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| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ GhV2015a | Serial | 2715 | ||
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| Author | Ciprian Corneanu; Marc Oliu; Jeffrey F. Cohn; Sergio Escalera | ||||
| Title | Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History | Type | Journal Article | ||
| Year | 2016 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 28 | Issue | 8 | Pages | 1548-1568 |
| Keywords | Facial expression; affect; emotion recognition; RGB; 3D; thermal; multimodal | ||||
| Abstract | Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research. | ||||
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| Notes | HuPBA;MILAB; | Approved | no | ||
| Call Number | Admin @ si @ COC2016 | Serial | 2718 | ||
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| Author | Fadi Dornaika; Bogdan Raducanu; Alireza Bosaghzadeh | ||||
| Title | Facial expression recognition based on multi observations with application to social robotics | Type | Book Chapter | ||
| Year | 2015 | Publication | Emotional and Facial Expressions: Recognition, Developmental Differences and Social Importance | Abbreviated Journal | |
| Volume | Issue | Pages | 153-166 | ||
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| Abstract | Human-robot interaction is a hot topic nowadays in the social robotics
community. One crucial aspect is represented by the affective communication which comes encoded through the facial expressions. In this chapter, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, viewand texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial expression. |
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| Publisher | Nova Science publishers | Place of Publication | Editor | Bruce Flores | |
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| Notes | LAMP; | Approved | no | ||
| Call Number | Admin @ si @ DRB2015 | Serial | 2720 | ||
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| Author | Juan Ramon Terven Salinas; Bogdan Raducanu; Maria Elena Meza-de-Luna; Joaquin Salas | ||||
| Title | Head-gestures mirroring detection in dyadic social linteractions with computer vision-based wearable devices | Type | Journal Article | ||
| Year | 2016 | Publication | Neurocomputing | Abbreviated Journal | NEUCOM |
| Volume | 175 | Issue | B | Pages | 866–876 |
| Keywords | Head gestures recognition; Mirroring detection; Dyadic social interaction analysis; Wearable devices | ||||
| Abstract | During face-to-face human interaction, nonverbal communication plays a fundamental role. A relevant aspect that takes part during social interactions is represented by mirroring, in which a person tends to mimic the non-verbal behavior (head and body gestures, vocal prosody, etc.) of the counterpart. In this paper, we introduce a computer vision-based system to detect mirroring in dyadic social interactions with the use of a wearable platform. In our context, mirroring is inferred as simultaneous head noddings displayed by the interlocutors. Our approach consists of the following steps: (1) facial features extraction; (2) facial features stabilization; (3) head nodding recognition; and (4) mirroring detection. Our system achieves a mirroring detection accuracy of 72% on a custom mirroring dataset. | ||||
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| Notes | LAMP; 600.072; 600.068; | Approved | no | ||
| Call Number | Admin @ si @ TRM2016 | Serial | 2721 | ||
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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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| Area | Expedition | Conference | ICCVW | ||
| Notes | LAMP; 600.068; 600.072; | Approved | no | ||
| Call Number | Admin @ si @ TRM2015 | Serial | 2722 | ||
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| Author | M. Campos-Taberner; Adriana Romero; Carlo Gatta; Gustavo Camps-Valls | ||||
| Title | Shared feature representations of LiDAR and optical images: Trading sparsity for semantic discrimination | Type | Conference Article | ||
| Year | 2015 | Publication | IEEE International Geoscience and Remote Sensing Symposium IGARSS2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 4169 - 4172 | ||
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| Abstract | This paper studies the level of complementary information conveyed by extremely high resolution LiDAR and optical images. We pursue this goal following an indirect approach via unsupervised spatial-spectral feature extraction. We used a recently presented unsupervised convolutional neural network trained to enforce both population and lifetime spar-sity in the feature representation. We derived independent and joint feature representations, and analyzed the sparsity scores and the discriminative power. Interestingly, the obtained results revealed that the RGB+LiDAR representation is no longer sparse, and the derived basis functions merge color and elevation yielding a set of more expressive colored edge filters. The joint feature representation is also more discriminative when used for clustering and topological data visualization. | ||||
| Address | Milan; Italy; July 2015 | ||||
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| Area | Expedition | Conference | IGARSS | ||
| Notes | LAMP; 600.079;MILAB | Approved | no | ||
| Call Number | Admin @ si @ CRG2015 | Serial | 2724 | ||
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| Author | R. Bertrand; Oriol Ramos Terrades; P. Gomez-Kramer; P. Franco; Jean-Marc Ogier | ||||
| Title | A Conditional Random Field model for font forgery detection | Type | Conference Article | ||
| Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 576 - 580 | ||
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| Abstract | Nowadays, document forgery is becoming a real issue. A large amount of documents that contain critical information as payment slips, invoices or contracts, are constantly subject to fraudster manipulation because of the lack of security regarding this kind of document. Previously, a system to detect fraudulent documents based on its intrinsic features has been presented. It was especially designed to retrieve copy-move forgery and imperfection due to fraudster manipulation. However, when a set of characters is not present in the original document, copy-move forgery is not feasible. Hence, the fraudster will use a text toolbox to add or modify information in the document by imitating the font or he will cut and paste characters from another document where the font properties are similar. This often results in font type errors. Thus, a clue to detect document forgery consists of finding characters, words or sentences in a document with font properties different from their surroundings. To this end, we present in this paper an automatic forgery detection method based on document font features. Using the Conditional Random Field a measurement of probability that a character belongs to a specific font is made by comparing the character font features to a knowledge database. Then, the character is classified as a genuine or a fake one by comparing its probability to belong to a certain font type with those of the neighboring characters. | ||||
| Address | Nancy; France; August 2015 | ||||
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| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ BRG2015 | Serial | 2725 | ||
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| Author | Lluis Pere de las Heras; Oriol Ramos Terrades; Josep Llados; David Fernandez; Cristina Cañero | ||||
| Title | Use case visual Bag-of-Words techniques for camera based identity document classification | Type | Conference Article | ||
| Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 721 - 725 | ||
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| Abstract | Nowadays, automatic identity document recognition, including passport and driving license recognition, is at the core of many applications within the administrative and service sectors, such as police, hospitality, car renting, etc. In former years, the document information was manually extracted whereas today this data is recognized automatically from images obtained by flat-bed scanners. Yet, since these scanners tend to be expensive and voluminous, companies in the sector have recently turned their attention to cheaper, small and yet computationally powerful scanners: the mobile devices. The document identity recognition from mobile images enclose several new difficulties w.r.t traditional scanned images, such as the loss of a controlled background, perspective, blurring, etc. In this paper we present a real application for identity document classification of images taken from mobile devices. This classification process is of extreme importance since a prior knowledge of the document type and origin strongly facilitates the subsequent information extraction. The proposed method is based on a traditional Bagof-Words in which we have taken into consideration several key aspects to enhance recognition rate. The method performance has been studied on three datasets containing more than 2000 images from 129 different document classes. | ||||
| Address | Nancy; France; August 2015 | ||||
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| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.077; 600.061; | Approved | no | ||
| Call Number | Admin @ si @ HRL2015a | Serial | 2726 | ||
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| Author | Lluis Pere de las Heras; Oriol Ramos Terrades; Josep Llados | ||||
| Title | Attributed Graph Grammar for floor plan analysis | Type | Conference Article | ||
| Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 726 - 730 | ||
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| Abstract | In this paper, we propose the use of an Attributed Graph Grammar as unique framework to model and recognize the structure of floor plans. This grammar represents a building as a hierarchical composition of structurally and semantically related elements, where common representations are learned stochastically from annotated data. Given an input image, the parsing consists on constructing that graph representation that better agrees with the probabilistic model defined by the grammar. The proposed method provides several advantages with respect to the traditional floor plan analysis techniques. It uses an unsupervised statistical approach for detecting walls that adapts to different graphical notations and relaxes strong structural assumptions such are straightness and orthogonality. Moreover, the independence between the knowledge model and the parsing implementation allows the method to learn automatically different building configurations and thus, to cope the existing variability. These advantages are clearly demonstrated by comparing it with the most recent floor plan interpretation techniques on 4 datasets of real floor plans with different notations. | ||||
| Address | Nancy; France; August 2015 | ||||
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| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.077; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ HRL2015b | Serial | 2727 | ||
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| Author | Jiaolong Xu; David Vazquez; Krystian Mikolajczyk; Antonio Lopez | ||||
| Title | Hierarchical online domain adaptation of deformable part-based models | Type | Conference Article | ||
| Year | 2016 | Publication | IEEE International Conference on Robotics and Automation | Abbreviated Journal | |
| Volume | Issue | Pages | 5536-5541 | ||
| Keywords | Domain Adaptation; Pedestrian Detection | ||||
| Abstract | We propose an online domain adaptation method for the deformable part-based model (DPM). The online domain adaptation is based on a two-level hierarchical adaptation tree, which consists of instance detectors in the leaf nodes and a category detector at the root node. Moreover, combined with a multiple object tracking procedure (MOT), our proposal neither requires target-domain annotated data nor revisiting the source-domain data for performing the source-to-target domain adaptation of the DPM. From a practical point of view this means that, given a source-domain DPM and new video for training on a new domain without object annotations, our procedure outputs a new DPM adapted to the domain represented by the video. As proof-of-concept we apply our proposal to the challenging task of pedestrian detection. In this case, each instance detector is an exemplar classifier trained online with only one pedestrian per frame. The pedestrian instances are collected by MOT and the hierarchical model is constructed dynamically according to the pedestrian trajectories. Our experimental results show that the adapted detector achieves the accuracy of recent supervised domain adaptation methods (i.e., requiring manually annotated targetdomain data), and improves the source detector more than 10 percentage points. | ||||
| Address | Stockholm; Sweden; May 2016 | ||||
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| Area | Expedition | Conference | ICRA | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ XVM2016 | Serial | 2728 | ||
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| Author | Aura Hernandez-Sabate; Meritxell Joanpere; Nuria Gorgorio; Lluis Albarracin | ||||
| Title | Mathematics learning opportunities when playing a Tower Defense Game | Type | Journal | ||
| Year | 2015 | Publication | International Journal of Serious Games | Abbreviated Journal | IJSG |
| Volume | 2 | Issue | 4 | Pages | 57-71 |
| Keywords | Tower Defense game; learning opportunities; mathematics; problem solving; game design | ||||
| Abstract | A qualitative research study is presented herein with the purpose of identifying mathematics learning opportunities in students between 10 and 12 years old while playing a commercial version of a Tower Defense game. These learning opportunities are understood as mathematicisable moments of the game and involve the establishment of relationships between the game and mathematical problem solving. Based on the analysis of these mathematicisable moments, we conclude that the game can promote problem-solving processes and learning opportunities that can be associated with different mathematical contents that appears in mathematics curricula, thought it seems that teacher or new game elements might be needed to facilitate the processes. | ||||
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| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ HJG2015 | Serial | 2730 | ||
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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 | Gloria Fernandez Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; Henry Cordova; Cristina Sanchez Montes; I.Araujo ; Maria Lopez Ceron; J.Llach; F. Javier Sanchez | ||||
| Title | Colonic polyps are correctly identified by a computer vision method using wm-dova energy maps | Type | Conference Article | ||
| Year | 2015 | Publication | Proceedings of 23 United European- UEG Week 2015 | Abbreviated Journal | |
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| Area | Expedition | Conference | UEG | ||
| Notes | MV; IAM; 600.075;SIAI | Approved | no | ||
| Call Number | Admin @ si @ FBR2015 | Serial | 2732 | ||
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