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Author | Albert Ali Salah; E. Pauwels; R. Tavenard; Theo Gevers | ||||
Title | T-Patterns Revisited: Mining for Temporal Patterns in Sensor Data | Type | Journal Article | ||
Year | 2010 | Publication | Sensors | Abbreviated Journal | SENS |
Volume | 10 | Issue | 8 | Pages | 7496-7513 |
Keywords | sensor networks; temporal pattern extraction; T-patterns; Lempel-Ziv; Gaussian mixture model; MERL motion data | ||||
Abstract | The trend to use large amounts of simple sensors as opposed to a few complex sensors to monitor places and systems creates a need for temporal pattern mining algorithms to work on such data. The methods that try to discover re-usable and interpretable patterns in temporal event data have several shortcomings. We contrast several recent approaches to the problem, and extend the T-Pattern algorithm, which was previously applied for detection of sequential patterns in behavioural sciences. The temporal complexity of the T-pattern approach is prohibitive in the scenarios we consider. We remedy this with a statistical model to obtain a fast and robust algorithm to find patterns in temporal data. We test our algorithm on a recent database collected with passive infrared sensors with millions of events. | ||||
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Notes | ALTRES;ISE | Approved | no | ||
Call Number | Admin @ si @ SPT2010 | Serial | 1845 | ||
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Author | Naveen Onkarappa; Angel Sappa | ||||
Title | Synthetic sequences and ground-truth flow field generation for algorithm validation | Type | Journal Article | ||
Year | 2015 | Publication | Multimedia Tools and Applications | Abbreviated Journal | MTAP |
Volume | 74 | Issue | 9 | Pages | 3121-3135 |
Keywords | Ground-truth optical flow; Synthetic sequence; Algorithm validation | ||||
Abstract | Research in computer vision is advancing by the availability of good datasets that help to improve algorithms, validate results and obtain comparative analysis. The datasets can be real or synthetic. For some of the computer vision problems such as optical flow it is not possible to obtain ground-truth optical flow with high accuracy in natural outdoor real scenarios directly by any sensor, although it is possible to obtain ground-truth data of real scenarios in a laboratory setup with limited motion. In this difficult situation computer graphics offers a viable option for creating realistic virtual scenarios. In the current work we present a framework to design virtual scenes and generate sequences as well as ground-truth flow fields. Particularly, we generate a dataset containing sequences of driving scenarios. The sequences in the dataset vary in different speeds of the on-board vision system, different road textures, complex motion of vehicle and independent moving vehicles in the scene. This dataset enables analyzing and adaptation of existing optical flow methods, and leads to invention of new approaches particularly for driver assistance systems. | ||||
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Publisher | Springer US | Place of Publication | Editor | ||
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ISSN | 1380-7501 | ISBN | Medium | ||
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Notes | ADAS; 600.055; 601.215; 600.076 | Approved | no | ||
Call Number | Admin @ si @ OnS2014b | Serial | 2472 | ||
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Author | Lichao Zhang; Abel Gonzalez-Garcia; Joost Van de Weijer; Martin Danelljan; Fahad Shahbaz Khan | ||||
Title | Synthetic Data Generation for End-to-End Thermal Infrared Tracking | Type | Journal Article | ||
Year | 2019 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 28 | Issue | 4 | Pages | 1837 - 1850 |
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Abstract | The usage of both off-the-shelf and end-to-end trained deep networks have significantly improved the performance of visual tracking on RGB videos. However, the lack of large labeled datasets hampers the usage of convolutional neural networks for tracking in thermal infrared (TIR) images. Therefore, most state-of-the-art methods on tracking for TIR data are still based on handcrafted features. To address this problem, we propose to use image-to-image translation models. These models allow us to translate the abundantly available labeled RGB data to synthetic TIR data. We explore both the usage of paired and unpaired image translation models for this purpose. These methods provide us with a large labeled dataset of synthetic TIR sequences, on which we can train end-to-end optimal features for tracking. To the best of our knowledge, we are the first to train end-to-end features for TIR tracking. We perform extensive experiments on the VOT-TIR2017 dataset. We show that a network trained on a large dataset of synthetic TIR data obtains better performance than one trained on the available real TIR data. Combining both data sources leads to further improvement. In addition, when we combine the network with motion features, we outperform the state of the art with a relative gain of over 10%, clearly showing the efficiency of using synthetic data to train end-to-end TIR trackers. | ||||
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Notes | LAMP; 600.141; 600.120 | Approved | no | ||
Call Number | Admin @ si @ YGW2019 | Serial | 3228 | ||
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Author | Marçal Rusiñol; Josep Llados; Gemma Sanchez | ||||
Title | Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings | Type | Journal Article | ||
Year | 2010 | Publication | Pattern Analysis and Applications | Abbreviated Journal | PAA |
Volume | 13 | Issue | 3 | Pages | 321-331 |
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Abstract | In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes. | ||||
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Publisher | Springer-Verlag | Place of Publication | Editor | ||
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Series Volume | Series Issue | Edition | |||
ISSN | 1433-7541 | ISBN | Medium | ||
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Notes | DAG | Approved | no | ||
Call Number | DAG @ dag @ RLS2010 | Serial | 1165 | ||
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Author | Josep Llados; Enric Marti; Juan J.Villanueva | ||||
Title | Symbol recognition by error-tolerant subgraph matching between region adjacency graphs | Type | Journal Article | ||
Year | 2001 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | |
Volume | 23 | Issue | 10 | Pages | 1137-1143 |
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Abstract | The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. | ||||
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Notes | DAG;IAM;ISE; | Approved | no | ||
Call Number | IAM @ iam @ LMV2001 | Serial | 1581 | ||
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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 | David Geronimo; Antonio Lopez; Angel Sappa; Thorsten Graf | ||||
Title | Survey on Pedestrian Detection for Advanced Driver Assistance Systems | Type | Journal Article | ||
Year | 2010 | Publication | IEEE Transaction on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 32 | Issue | 7 | Pages | 1239–1258 |
Keywords | ADAS, pedestrian detection, on-board vision, survey | ||||
Abstract | Advanced driver assistance systems (ADASs), and particularly pedestrian protection systems (PPSs), have become an active research area aimed at improving traffic safety. The major challenge of PPSs is the development of reliable on-board pedestrian detection systems. Due to the varying appearance of pedestrians (e.g., different clothes, changing size, aspect ratio, and dynamic shape) and the unstructured environment, it is very difficult to cope with the demanded robustness of this kind of system. Two problems arising in this research area are the lack of public benchmarks and the difficulty in reproducing many of the proposed methods, which makes it difficult to compare the approaches. As a result, surveying the literature by enumerating the proposals one-after-another is not the most useful way to provide a comparative point of view. Accordingly, we present a more convenient strategy to survey the different approaches. We divide the problem of detecting pedestrians from images into different processing steps, each with attached responsibilities. Then, the different proposed methods are analyzed and classified with respect to each processing stage, favoring a comparative viewpoint. Finally, discussion of the important topics is presented, putting special emphasis on the future needs and challenges. | ||||
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ISSN | 0162-8828 | ISBN | Medium | ||
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Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ GLS2010 | Serial | 1340 | ||
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Author | Fatemeh Noroozi; Ciprian Corneanu; Dorota Kamińska; Tomasz Sapiński; Sergio Escalera; Gholamreza Anbarjafari | ||||
Title | Survey on Emotional Body Gesture Recognition | Type | Journal Article | ||
Year | 2021 | Publication | IEEE Transactions on Affective Computing | Abbreviated Journal | TAC |
Volume | 12 | Issue | 2 | Pages | 505 - 523 |
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Abstract | Automatic emotion recognition has become a trending research topic in the past decade. While works based on facial expressions or speech abound, recognizing affect from body gestures remains a less explored topic. We present a new comprehensive survey hoping to boost research in the field. We first introduce emotional body gestures as a component of what is commonly known as “body language” and comment general aspects as gender differences and culture dependence. We then define a complete framework for automatic emotional body gesture recognition. We introduce person detection and comment static and dynamic body pose estimation methods both in RGB and 3D. We then comment the recent literature related to representation learning and emotion recognition from images of emotionally expressive gestures. We also discuss multi-modal approaches that combine speech or face with body gestures for improved emotion recognition. While pre-processing methodologies (e.g. human detection and pose estimation) are nowadays mature technologies fully developed for robust large scale analysis, we show that for emotion recognition the quantity of labelled data is scarce, there is no agreement on clearly defined output spaces and the representations are shallow and largely based on naive geometrical representations. | ||||
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Notes | HUPBA; no proj | Approved | no | ||
Call Number | Admin @ si @ NCK2021 | Serial | 3657 | ||
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Author | Hao Fang; Ajian Liu; Jun Wan; Sergio Escalera; Chenxu Zhao; Xu Zhang; Stan Z Li; Zhen Lei | ||||
Title | Surveillance Face Anti-spoofing | Type | Journal Article | ||
Year | 2024 | Publication | IEEE Transactions on Information Forensics and Security | Abbreviated Journal | TIFS |
Volume | 19 | Issue | Pages | 1535-1546 | |
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Abstract | Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, recent research generally focuses on short-distance applications (i.e., phone unlocking) while lacking consideration of long-distance scenes (i.e., surveillance security checks). In order to promote relevant research and fill this gap in the community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask) dataset captured under 40 surveillance scenes, which has 101 subjects from different age groups with 232 3D attacks (high-fidelity masks), 200 2D attacks (posters, portraits, and screens), and 2 adversarial attacks. In this scene, low image resolution and noise interference are new challenges faced in surveillance FAS. Together with the SuHiFiMask dataset, we propose a Contrastive Quality-Invariance Learning (CQIL) network to alleviate the performance degradation caused by image quality from three aspects: (1) An Image Quality Variable module (IQV) is introduced to recover image information associated with discrimination by combining the super-resolution network. (2) Using generated sample pairs to simulate quality variance distributions to help contrastive learning strategies obtain robust feature representation under quality variation. (3) A Separate Quality Network (SQN) is designed to learn discriminative features independent of image quality. Finally, a large number of experiments verify the quality of the SuHiFiMask dataset and the superiority of the proposed CQIL. | ||||
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Notes | HUPBA | Approved | no | ||
Call Number | Admin @ si @ FLW2024 | Serial | 3869 | ||
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Author | Xavier Perez Sala; Fernando De la Torre; Laura Igual; Sergio Escalera; Cecilio Angulo | ||||
Title | Subspace Procrustes Analysis | Type | Journal Article | ||
Year | 2017 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
Volume | 121 | Issue | 3 | Pages | 327–343 |
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Abstract | Procrustes Analysis (PA) has been a popular technique to align and build 2-D statistical models of shapes. Given a set of 2-D shapes PA is applied to remove rigid transformations. Then, a non-rigid 2-D model is computed by modeling (e.g., PCA) the residual. Although PA has been widely used, it has several limitations for modeling 2-D shapes: occluded landmarks and missing data can result in local minima solutions, and there is no guarantee that the 2-D shapes provide a uniform sampling of the 3-D space of rotations for the object. To address previous issues, this paper proposes Subspace PA (SPA). Given several
instances of a 3-D object, SPA computes the mean and a 2-D subspace that can simultaneously model all rigid and non-rigid deformations of the 3-D object. We propose a discrete (DSPA) and continuous (CSPA) formulation for SPA, assuming that 3-D samples of an object are provided. DSPA extends the traditional PA, and produces unbiased 2-D models by uniformly sampling different views of the 3-D object. CSPA provides a continuous approach to uniformly sample the space of 3-D rotations, being more efficient in space and time. Experiments using SPA to learn 2-D models of bodies from motion capture data illustrate the benefits of our approach. |
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Notes | MILAB; HuPBA; no proj | Approved | no | ||
Call Number | Admin @ si @ PTI2017 | Serial | 2841 | ||
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Author | Thanh Nam Le; Muhammad Muzzamil Luqman; Anjan Dutta; Pierre Heroux; Christophe Rigaud; Clement Guerin; Pasquale Foggia; Jean Christophe Burie; Jean Marc Ogier; Josep Llados; Sebastien Adam | ||||
Title | Subgraph spotting in graph representations of comic book images | Type | Journal Article | ||
Year | 2018 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 112 | Issue | Pages | 118-124 | |
Keywords | Attributed graph; Region adjacency graph; Graph matching; Graph isomorphism; Subgraph isomorphism; Subgraph spotting; Graph indexing; Graph retrieval; Query by example; Dataset and comic book images | ||||
Abstract | Graph-based representations are the most powerful data structures for extracting, representing and preserving the structural information of underlying data. Subgraph spotting is an interesting research problem, especially for studying and investigating the structural information based content-based image retrieval (CBIR) and query by example (QBE) in image databases. In this paper we address the problem of lack of freely available ground-truthed datasets for subgraph spotting and present a new dataset for subgraph spotting in graph representations of comic book images (SSGCI) with its ground-truth and evaluation protocol. Experimental results of two state-of-the-art methods of subgraph spotting are presented on the new SSGCI dataset. | ||||
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Notes | DAG; 600.097; 600.121 | Approved | no | ||
Call Number | Admin @ si @ LLD2018 | Serial | 3150 | ||
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Author | Debora Gil; Aura Hernandez-Sabate; Mireia Brunat;Steven Jansen; Jordi Martinez-Vilalta | ||||
Title | Structure-preserving smoothing of biomedical images | Type | Journal Article | ||
Year | 2011 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 44 | Issue | 9 | Pages | 1842-1851 |
Keywords | Non-linear smoothing; Differential geometry; Anatomical structures; segmentation; Cardiac magnetic resonance; Computerized tomography | ||||
Abstract | Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. | ||||
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ISSN | 0031-3203 | ISBN | Medium | ||
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Notes | IAM; ADAS | Approved | no | ||
Call Number | IAM @ iam @ GHB2011 | Serial | 1526 | ||
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Author | Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Benedi | ||||
Title | Structure Detection and Segmentation of Documents Using 2D Stochastic Context-Free Grammars | Type | Journal Article | ||
Year | 2015 | Publication | Neurocomputing | Abbreviated Journal | NEUCOM |
Volume | 150 | Issue | A | Pages | 147-154 |
Keywords | document image analysis; stochastic context-free grammars; text classication features | ||||
Abstract | In this paper we dene a bidimensional extension of Stochastic Context-Free Grammars for structure detection and segmentation of images of documents.
Two sets of text classication features are used to perform an initial classication of each zone of the page. Then, the document segmentation is obtained as the most likely hypothesis according to a stochastic grammar. We used a dataset of historical marriage license books to validate this approach. We also tested several inference algorithms for Probabilistic Graphical Models and the results showed that the proposed grammatical model outperformed the other methods. Furthermore, grammars also provide the document structure along with its segmentation. |
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Notes | DAG; 601.158; 600.077; 600.061 | Approved | no | ||
Call Number | Admin @ si @ ACS2015 | Serial | 2531 | ||
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Author | Domicele Jonauskaite; Nele Dael; C. Alejandro Parraga; Laetitia Chevre; Alejandro Garcia Sanchez; Christine Mohr | ||||
Title | Stripping #The Dress: The importance of contextual information on inter-individual differences in colour perception | Type | Journal Article | ||
Year | 2018 | Publication | Psychological Research | Abbreviated Journal | PSYCHO R |
Volume | Issue | Pages | 1-15 | ||
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Abstract | In 2015, a picture of a Dress (henceforth the Dress) triggered popular and scientific interest; some reported seeing the Dress in white and gold (W&G) and others in blue and black (B&B). We aimed to describe the phenomenon and investigate the role of contextualization. Few days after the Dress had appeared on the Internet, we projected it to 240 students on two large screens in the classroom. Participants reported seeing the Dress in B&B (48%), W&G (38%), or blue and brown (B&Br; 7%). Amongst numerous socio-demographic variables, we only observed that W&G viewers were most likely to have always seen the Dress as W&G. In the laboratory, we tested how much contextual information is necessary for the phenomenon to occur. Fifty-seven participants selected colours most precisely matching predominant colours of parts or the full Dress. We presented, in this order, small squares (a), vertical strips (b), and the full Dress (c). We found that (1) B&B, B&Br, and W&G viewers had selected colours differing in lightness and chroma levels for contextualized images only (b, c conditions) and hue for fully contextualized condition only (c) and (2) B&B viewers selected colours most closely matching displayed colours of the Dress. Thus, the Dress phenomenon emerges due to inter-individual differences in subjectively perceived lightness, chroma, and hue, at least when all aspects of the picture need to be integrated. Our results support the previous conclusions that contextual information is key to colour perception; it should be important to understand how this actually happens. | ||||
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Notes | NEUROBIT; no proj | Approved | no | ||
Call Number | Admin @ si @ JDP2018 | Serial | 3149 | ||
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Author | Mariella Dimiccoli; Benoît Girard; Alain Berthoz; Daniel Bennequin | ||||
Title | Striola Magica: a functional explanation of otolith organs | Type | Journal Article | ||
Year | 2013 | Publication | Journal of Computational Neuroscience | Abbreviated Journal | JCN |
Volume | 35 | Issue | 2 | Pages | 125-154 |
Keywords | Otolith organs ;Striola; Vestibular pathway | ||||
Abstract | Otolith end organs of vertebrates sense linear accelerations of the head and gravitation. The hair cells on their epithelia are responsible for transduction. In mammals, the striola, parallel to the line where hair cells reverse their polarization, is a narrow region centered on a curve with curvature and torsion. It has been shown that the striolar region is functionally different from the rest, being involved in a phasic vestibular pathway. We propose a mathematical and computational model that explains the necessity of this amazing geometry for the striola to be able to carry out its function. Our hypothesis, related to the biophysics of the hair cells and to the physiology of their afferent neurons, is that striolar afferents collect information from several type I hair cells to detect the jerk in a large domain of acceleration directions. This predicts a mean number of two calyces for afferent neurons, as measured in rodents. The domain of acceleration directions sensed by our striolar model is compatible with the experimental results obtained on monkeys considering all afferents. Therefore, the main result of our study is that phasic and tonic vestibular afferents cover the same geometrical fields, but at different dynamical and frequency domains. | ||||
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Publisher | Springer US | Place of Publication | Editor | ||
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ISSN | 1573-6873. 2013 | ISBN | Medium | ||
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @DBG2013 | Serial | 2787 | ||
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