|
Marc Castello, Jordi Gonzalez, Ariel Amato, Pau Baiget, Carles Fernandez, Josep M. Gonfaus, et al. (2013). Exploiting Multimodal Interaction Techniques for Video-Surveillance. In Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library (Vol. 48, pp. 135–151). Springer Berlin Heidelberg.
Abstract: In this paper we present an example of a video surveillance application that exploits Multimodal Interactive (MI) technologies. The main objective of the so-called VID-Hum prototype was to develop a cognitive artificial system for both the detection and description of a particular set of human behaviours arising from real-world events. The main procedure of the prototype described in this chapter entails: (i) adaptation, since the system adapts itself to the most common behaviours (qualitative data) inferred from tracking (quantitative data) thus being able to recognize abnormal behaviors; (ii) feedback, since an advanced interface based on Natural Language understanding allows end-users the communicationwith the prototype by means of conceptual sentences; and (iii) multimodality, since a virtual avatar has been designed to describe what is happening in the scene, based on those textual interpretations generated by the prototype. Thus, the MI methodology has provided an adequate framework for all these cooperating processes.
|
|
|
Lluis Pere de las Heras, David Fernandez, Alicia Fornes, Ernest Valveny, Gemma Sanchez, & Josep Llados. (2014). Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans. In Graphics Recognition. Current Trends and Challenges (Vol. 8746, pp. 135–146). LNCS. Springer Berlin Heidelberg.
Abstract: This paper proposes a runlength histogram signature as a perceptual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query, similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Additional retrieval results on sketched building’s facades are reported qualitatively in this paper. Its good description and its adaptability to two different sketch drawings despite its simplicity shows the interest of the proposed approach and opens a challenging research line in graphics recognition.
Keywords: Graphics recognition; Graphics retrieval; Image classification
|
|
|
Debora Gil, F. Javier Sanchez, Gloria Fernandez Esparrach, & Jorge Bernal. (2015). 3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos. In Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 (Vol. 9515, pp. 140–152). LNCS.
Abstract: Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select
those image regions presenting the highest stable spatio-temporal response.
Spatio-temporal stability is achieved by extracting 3D watershed regions on the
temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection.
Keywords: Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds
|
|
|
Javier Marin, David Geronimo, David Vazquez, & Antonio Lopez. (2012). Pedestrian Detection: Exploring Virtual Worlds. In Handbook of Pattern Recognition: Methods and Application (Vol. 5, pp. 145–162). iConcept Press.
Abstract: Handbook of pattern recognition will include contributions from university educators and active research experts. This Handbook is intended to serve as a basic reference on methods and applications of pattern recognition. The primary aim of this handbook is providing the community of pattern recognition with a readable, easy to understand resource that covers introductory, intermediate and advanced topics with equal clarity. Therefore, the Handbook of pattern recognition can serve equally well as reference resource and as classroom textbook. Contributions cover all methods, techniques and applications of pattern recognition. A tentative list of relevant topics might include: 1- Statistical, structural, syntactic pattern recognition. 2- Neural networks, machine learning, data mining. 3- Discrete geometry, algebraic, graph-based techniques for pattern recognition. 4- Face recognition, Signal analysis, image coding and processing, shape and texture analysis. 5- Document processing, text and graphics recognition, digital libraries. 6- Speech recognition, music analysis, multimedia systems. 7- Natural language analysis, information retrieval. 8- Biometrics, biomedical pattern analysis and information systems. 9- Other scientific, engineering, social and economical applications of pattern recognition. 10- Special hardware architectures, software packages for pattern recognition.
Keywords: Virtual worlds; Pedestrian Detection; Domain Adaptation
|
|
|
Josep Llados, Jaime Lopez-Krahe, & Enric Marti. (1997). A system to understand hand-drawn floor plans using subgraph isomorphism and Hough transform. In Machine Vision and Applications (Vol. 10, pp. 150–158).
Abstract: Presently, man-machine interface development is a widespread research activity. A system to understand hand drawn architectural drawings in a CAD environment is presented in this paper. To understand a document, we have to identify its building elements and their structural properties. An attributed graph structure is chosen as a symbolic representation of the input document and the patterns to recognize in it. An inexact subgraph isomorphism procedure using relaxation labeling techniques is performed. In this paper we focus on how to speed up the matching. There is a building element, the walls, characterized by a hatching pattern. Using a straight line Hough transform (SLHT)-based method, we recognize this pattern, characterized by parallel straight lines, and remove from the input graph the edges belonging to this pattern. The isomorphism is then applied to the remainder of the input graph. When all the building elements have been recognized, the document is redrawn, correcting the inaccurate strokes obtained from a hand-drawn input.
Keywords: Line drawings – Hough transform – Graph matching – CAD systems – Graphics recognition
|
|
|
Nataliya Shapovalova, Carles Fernandez, Xavier Roca, & Jordi Gonzalez. (2011). Semantics of Human Behavior in Image Sequences. In Albert Ali Salah, & (Ed.), Computer Analysis of Human Behavior (pp. 151–182). Springer London.
Abstract: Human behavior is contextualized and understanding the scene of an action is crucial for giving proper semantics to behavior. In this chapter we present a novel approach for scene understanding. The emphasis of this work is on the particular case of Human Event Understanding. We introduce a new taxonomy to organize the different semantic levels of the Human Event Understanding framework proposed. Such a framework particularly contributes to the scene understanding domain by (i) extracting behavioral patterns from the integrative analysis of spatial, temporal, and contextual evidence and (ii) integrative analysis of bottom-up and top-down approaches in Human Event Understanding. We will explore how the information about interactions between humans and their environment influences the performance of activity recognition, and how this can be extrapolated to the temporal domain in order to extract higher inferences from human events observed in sequences of images.
|
|
|
Juan Ramon Terven Salinas, Joaquin Salas, & Bogdan Raducanu. (2014). Robust Head Gestures Recognition for Assistive Technology. In Pattern Recognition (Vol. 8495, pp. 152–161). LNCS. Springer International Publishing.
Abstract: This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture.
|
|
|
Fadi Dornaika, Bogdan Raducanu, & Alireza Bosaghzadeh. (2015). Facial expression recognition based on multi observations with application to social robotics. In Bruce Flores (Ed.), Emotional and Facial Expressions: Recognition, Developmental Differences and Social Importance (pp. 153–166). Nova Science publishers.
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.
|
|
|
Fadi Dornaika, & Bogdan Raducanu. (2012). Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation. In S.E. Carter (Ed.), Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions (pp. 157–178). NOVA Publishers.
|
|
|
Enric Marti, Jordi Regincos, Juan Jose Villanueva, & Jaime Lopez-Krahe. (1994). Line drawing interpretation as polyhedral objects to man-machine interaction in CAD systems. In Advances in Pattern Recognition and Image Analysis, (pp. 158–169). World Scientific Pub.
|
|
|
David Roche, Debora Gil, & Jesus Giraldo. (2014). Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models? In G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology (Vol. 796, pp. 159–181). Springer Netherlands.
Abstract: Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists.
Keywords: β-arrestin; biased agonism; curve fitting; empirical modeling; evolutionary algorithm; functional selectivity; G protein; GPCR; Hill coefficient; intrinsic efficacy; inverse agonism; mathematical modeling; mechanistic modeling; operational model; parameter optimization; receptor dimer; receptor oligomerization; receptor constitutive activity; signal transduction; two-state model
|
|
|
Panagiota Spyridonos, Fernando Vilariño, Jordi Vitria, Fernando Azpiroz, & Petia Radeva. (2006). Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions. In and J. Sporring M. N. R. Larsen (Ed.), 9th International Conference on Medical Image Computing and Computer–Assisted Intervention (Vol. 4191, 161–168). LNCS. Berlin Heidelberg: Springer Verlag.
Abstract: Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of con- tractions and to analyze the intestine motility. Feature extraction is es- sential for getting efficient patterns to detect contractions in wireless video endoscopy of small intestine. We propose a novel method based on anisotropic image filtering and efficient statistical classification of con- traction features. In particular, we apply the image gradient tensor for mining informative skeletons from the original image and a sequence of descriptors for capturing the characteristic pattern of contractions. Fea- tures extracted from the endoluminal images were evaluated in terms of their discriminatory ability in correct classifying images as either belong- ing to contractions or not. Classification was performed by means of a support vector machine classifier with a radial basis function kernel. Our classification rates gave sensitivity of the order of 90.84% and specificity of the order of 94.43% respectively. These preliminary results highlight the high efficiency of the selected descriptors and support the feasibility of the proposed method in assisting the automatic detection and analysis of contractions.
|
|
|
David Vazquez, Antonio Lopez, Daniel Ponsa, & David Geronimo. (2013). Interactive Training of Human Detectors. In Multiodal Interaction in Image and Video Applications (Vol. 48, pp. 169–182). Springer Berlin Heidelberg.
Abstract: Image based human detection remains as a challenging problem. Most promising detectors rely on classifiers trained with labelled samples. However, labelling is a manual labor intensive step. To overcome this problem we propose to collect images of pedestrians from a virtual city, i.e., with automatic labels, and train a pedestrian detector with them, which works fine when such virtual-world data are similar to testing one, i.e., real-world pedestrians in urban areas. When testing data is acquired in different conditions than training one, e.g., human detection in personal photo albums, dataset shift appears. In previous work, we cast this problem as one of domain adaptation and solve it with an active learning procedure. In this work, we focus on the same problem but evaluating a different set of faster to compute features, i.e., Haar, EOH and their combination. In particular, we train a classifier with virtual-world data, using such features and Real AdaBoost as learning machine. This classifier is applied to real-world training images. Then, a human oracle interactively corrects the wrong detections, i.e., few miss detections are manually annotated and some false ones are pointed out too. A low amount of manual annotation is fixed as restriction. Real- and virtual-world difficult samples are combined within what we call cool world and we retrain the classifier with this data. Our experiments show that this adapted classifier is equivalent to the one trained with only real-world data but requiring 90% less manual annotations.
Keywords: Pedestrian Detection; Virtual World; AdaBoost; Domain Adaptation
|
|
|
Joan Mas, J.A. Jorge, Gemma Sanchez, & Josep Llados. (2008). Representing and Parsing Sketched Symbols using Adjacency Grammars and a Grid-Directed Parser. In J.M. Ogier J. L. W. Liu (Ed.), Graphics Recognition: Recent Advances and New Opportunities, (Vol. 5046, 176–187). LNCS.
|
|
|
Isabelle Guyon, Lisheng Sun Hosoya, Marc Boulle, Hugo Jair Escalante, Sergio Escalera, Zhengying Liu, et al. (2019). Analysis of the AutoML Challenge Series 2015-2018. In Automated Machine Learning (pp. 177–219). SSCML. Springer.
Abstract: The ChaLearn AutoML Challenge (The authors are in alphabetical order of last name, except the first author who did most of the writing and the second author who produced most of the numerical analyses and plots.) (NIPS 2015 – ICML 2016) consisted of six rounds of a machine learning competition of progressive difficulty, subject to limited computational resources. It was followed bya one-round AutoML challenge (PAKDD 2018). The AutoML setting differs from former model selection/hyper-parameter selection challenges, such as the one we previously organized for NIPS 2006: the participants aim to develop fully automated and computationally efficient systems, capable of being trained and tested without human intervention, with code submission. This chapter analyzes the results of these competitions and provides details about the datasets, which were not revealed to the participants. The solutions of the winners are systematically benchmarked over all datasets of all rounds and compared with canonical machine learning algorithms available in scikit-learn. All materials discussed in this chapter (data and code) have been made publicly available at http://automl.chalearn.org/.
|
|