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C. Alejandro Parraga, Jordi Roca, Dimosthenis Karatzas and Sophie Wuerger. 2014. Limitations of visual gamma corrections in LCD displays. Dis, 35(5), 227–239.
Abstract: A method for estimating the non-linear gamma transfer function of liquid–crystal displays (LCDs) without the need of a photometric measurement device was described by Xiao et al. (2011) [1]. It relies on observer’s judgments of visual luminance by presenting eight half-tone patterns with luminances from 1/9 to 8/9 of the maximum value of each colour channel. These half-tone patterns were distributed over the screen both over the vertical and horizontal viewing axes. We conducted a series of photometric and psychophysical measurements (consisting in the simultaneous presentation of half-tone patterns in each trial) to evaluate whether the angular dependency of the light generated by three different LCD technologies would bias the results of these gamma transfer function estimations. Our results show that there are significant differences between the gamma transfer functions measured and produced by observers at different viewing angles. We suggest appropriate modifications to the Xiao et al. paradigm to counterbalance these artefacts which also have the advantage of shortening the amount of time spent in collecting the psychophysical measurements.
Keywords: Display calibration; Psychophysics; Perceptual; Visual gamma correction; Luminance matching; Observer-based calibration
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Jon Almazan, Alicia Fornes and Ernest Valveny. 2012. A non-rigid appearance model for shape description and recognition. PR, 45(9), 3105–3113.
Abstract: In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach.
Keywords: Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition
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Josep Llados, Ernest Valveny, Gemma Sanchez and Enric Marti. 2003. A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa. Proceedings of Pattern Recognition in Information Systems. ICEIS Press, 1–13.
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Alicia Fornes and Josep Llados. 2010. A Symbol-dependent Writer Identifcation Approach in Old Handwritten Music Scores. 12th International Conference on Frontiers in Handwriting Recognition.634–639.
Abstract: Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we introduce a symbol-dependent approach for identifying the writer of old music scores, which is based on two symbol recognition methods. The main idea is to use the Blurred Shape Model descriptor and a DTW-based method for detecting, recognizing and describing the music clefs and notes. The proposed approach has been evaluated in a database of old music scores, achieving very high writer identification rates.
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J.Kuhn and 10 others. 2015. Advancing Physics Learning Through Traversing a Multi-Modal Experimentation Space. Workshop Proceedings on the 11th International Conference on Intelligent Environments.373–380.
Abstract: Translating conceptual knowledge into real world experiences presents a significant educational challenge. This position paper presents an approach that supports learners in moving seamlessly between conceptual learning and their application in the real world by bringing physical and virtual experiments into everyday settings. Learners are empowered in conducting these situated experiments in a variety of physical settings by leveraging state of the art mobile, augmented reality, and virtual reality technology. A blend of mobile-based multi-sensory physical experiments, augmented reality and enabling virtual environments can allow learners to bridge their conceptual learning with tangible experiences in a completely novel manner. This approach focuses on the learner by applying self-regulated personalised learning techniques, underpinned by innovative pedagogical approaches and adaptation techniques, to ensure that the needs and preferences of each learner are catered for individually.
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Alicia Fornes, Sergio Escalera, Josep Llados and Ernest Valveny. 2010. Symbol Classification using Dynamic Aligned Shape Descriptor. 20th International Conference on Pattern Recognition.1957–1960.
Abstract: Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we propose a new descriptor and distance computation for coping with the problem of symbol recognition in the domain of Graphical Document Image Analysis. The proposed D-Shape descriptor encodes the arrangement information of object parts in a circular structure, allowing different levels of distortion. The classification is performed using a cyclic Dynamic Time Warping based method, allowing distortions and rotation. The methodology has been validated on different data sets, showing very high recognition rates.
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Jaime Lopez-Krahe, Josep Llados and Enric Marti. 2000. Architectural Floor Plan Analysis. University of Edinburgh.
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Josep Llados, Ernest Valveny, Gemma Sanchez and Enric Marti. 2002. Symbol recognition: current advances and perspectives. In Dorothea Blostein and Young- Bin Kwon, ed. Graphics Recognition Algorithms And Applications. Springer-Verlag, 104–128. (LNCS.)
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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Josep Llados, Horst Bunke and Enric Marti. 1997. Using Cyclic String Matching to Find Rotational and Reflectional Symmetries in Shapes. Intelligent Robots: Sensing, Modeling and Planning. World Scientific Press, 164–179.
Abstract: Dagstuhl Workshop
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Kaida Xiao, Chenyang Fu, D.Mylonas, Dimosthenis Karatzas and S. Wuerger. 2013. Unique Hue Data for Colour Appearance Models. Part ii: Chromatic Adaptation Transform. CRA, 38(1), 22–29.
Abstract: Unique hue settings of 185 observers under three room-lighting conditions were used to evaluate the accuracy of full and mixed chromatic adaptation transform models of CIECAM02 in terms of unique hue reproduction. Perceptual hue shifts in CIECAM02 were evaluated for both models with no clear difference using the current Commission Internationale de l'Éclairage (CIE) recommendation for mixed chromatic adaptation ratio. Using our large dataset of unique hue data as a benchmark, an optimised parameter is proposed for chromatic adaptation under mixed illumination conditions that produces more accurate results in unique hue reproduction. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013
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