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Computer vision. --- Pattern recognition systems. --- Computer algorithms.

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The book presents three studies in which eye tracking data were collected at the Musée des Beaux-Arts in Rouen in June and July 2013. Overall, the results of those three studies highlight the knowledge gained from the analysis of the very first saccade in a museum context, when people look at paintings and statues. The first study analyzes how viewers orient their first saccade on paintings. This study shows that, in a museum, the first saccade is attracted toward the center of paintings. This attraction toward the paintings’ center is found in all the subjects’ groups that we have studied. Noteworthily, this effect is significantly less pronounced in individuals who never visit museums. It is among amateurs, who often visit museums, that the center attracts the most the first saccade. Among experts, painters or art history teachers, and to a lesser extent among amateurs, the pictorial composition largely determines the orientation of the first saccade. We indeed found that, as soon as the first saccade, experts orient their gaze toward the main subject. This phenomenon seems to be explained by the fact that experts immediately orient their gaze (here measured as the first saccade) toward the paintings’ location conveying the most meaning. It can either be the center, or a peripheral area, depending on whether the paintings’ most meaningful subject is located centrally or peripherally. The second study shows that the center does not attract the first saccade in 5-year-old children. This behavior appears later, in 8- to 10-year-old children. However, noticeably, the 8–10-year-old children orient significantly less frequently their first saccade toward the paintings’ center as adults do, and this is also true when one considers non-expert adult viewers. The results of the third study focus on statues and reveal a very different oculomotor behavior: Indeed, rather than looking at the center, statues’ viewers exhibit a clear tendency to saccade first at the statues’ contours. This stands in contrast with the behavior that we observe with paintings. Our study concludes that statues trigger a specific oculomotor behavior. The latter appears to be mostly driven by the physical presence that stone bodies incarnate. The movement and the climax of this movement, that sculptors manage to convey, thus turn out to attract the gaze in a unique fashion. The book concludes that the first saccade is a powerful indicator of the oculomotor behavior that greatly improves our comprehension of the unique relationship between a viewer and artworks.

Mathematical statistics --- Electronics --- Computer. Automation --- patroonherkenning --- factoranalyse --- signal processing --- signaalprocessoren --- signaalverwerking --- Signal processing. --- Psychobiology. --- Human behavior. --- Pattern recognition systems. --- Digital and Analog Signal Processing. --- Behavioral Neuroscience. --- Automated Pattern Recognition. --- Art

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This two volume set (CCIS 1776-1777) constitutes the refereed proceedings of the 7th International Conference on Computer Vision and Image Processing, CVIP 2022, held in Nagpur, India, November 4–6, 2022. The 110 full papers and 11 short papers were carefully reviewed and selected from 307 submissions. Out of 121 papers, 109 papers are included in this book. The topical scope of the two-volume set focuses on Medical Image Analysis, Image/ Video Processing for Autonomous Vehicles, Activity Detection/ Recognition, Human Computer Interaction, Segmentation and Shape Representation, Motion and Tracking, Image/ Video Scene Understanding, Image/Video Retrieval, Remote Sensing, Hyperspectral Image Processing, Face, Iris, Emotion, Sign Language and Gesture Recognition, etc.

Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- grafische vormgeving --- Image processing—Digital techniques. --- Computer vision. --- Computer Imaging, Vision, Pattern Recognition and Graphics.

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The aim of the conference is to present and discuss new methods, issues and challenges encountered in all parts of the complex process of gradual development and application of digital surface models. This process covers data capture, data generation, storage, model creation, validation, manipulation, utilization and visualization. Each stage requires suitable methods and involves issues that may substantially decrease the value of the model. Furthermore, the conference provides a platform to discuss the requirements, features and research approaches for 3D modeling, continuous field modeling and other geoscience applications. The conference covers the following topics: - LIDAR for elevation data - Radar interferometry for elevation data - Surface model creation - Surface model statistics - Surface model storage (including data formats, standardization, database) - Feature extraction - Analysis of surface models - Surface models for hydrology, meteorology, climatology - Surface models for signal spreading - Surface models for geology (structural, mining) - Surface models for environmental science - Surface models for visibility studies - Surface models for urban geography - Surface models for human geography - Uncertainty of surface models and digital terrain analysis - Surface model visual enhancement and rendering  .

Geodesy. Cartography --- Artificial intelligence. Robotics. Simulation. Graphics --- Geography --- geodesie --- GIS (geografisch informatiesysteem) --- grafische vormgeving --- Geographical information systems. --- Optical data processing. --- Geographical Information Systems/Cartography. --- Computer Imaging, Vision, Pattern Recognition and Graphics.

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This book discusses email spam detection and its challenges such as text classification and categorization. The book proposes an efficient spam detection technique that is a combination of Character Segmentation and Recognition and Classification (CSRC). The author describes how this can detect whether an email (text and image based) is a spam mail or not. The book presents four solutions: first, to extract the text character from the image by segmentation process which includes a combination of Discrete Wavelet Transform (DWT) and skew detection. Second, text characters are via text recognition and visual feature extraction approach which relies on contour analysis with improved Local Binary Pattern (LBP). Third, extracted text features are classified using improvised K-Nearest Neighbor search (KNN) and Support Vector Machine (SVM). Fourth, the performance of the proposed method is validated by the measure of metric named as sensitivity, specificity, precision, recall, F-measure, accuracy, error rate and correct rate. Presents solutions to email spam detection and discusses its challenges such as text classification and categorization; Analyzes the proposed techniques’ performance using precision, F-measure, recall and accuracy; Evaluates the limitations of the proposed research thereby recommending future research.

Telecommunication technology --- Mass communications --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- neuronale netwerken --- fuzzy logic --- cybernetica --- grafische vormgeving --- tekstverwerking --- algoritmen --- KI (kunstmatige intelligentie) --- communicatietechnologie --- Electrical engineering. --- Optical data processing. --- Computational intelligence. --- Algorithms. --- Communications Engineering, Networks. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Computational Intelligence.