Relevant bibliographies by topics / Human eye fixations; textured model

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Academic literature on the topic 'Human eye fixations; textured model'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Human eye fixations; textured model"

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Guo, Xiaoying, Liang Li, Akira Asano, and Chie Muraki Asano. "Influences of Global and Local Features on Eye-Movement Patterns in Visual-Similarity Perception of Synthesized Texture Images." Applied Sciences 10, no. 16 (2020): 5552. http://dx.doi.org/10.3390/app10165552.

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Global and local features are essential for visual-similarity texture perception. Therefore, understanding how people allocate their visual attention when viewing textures with global or local similarity is important. In this work, we investigate the influences of global and local features of a texture on eye-movement patterns and analyze the relationship between eye-movement patterns and visual-similarity selection. First, we synthesized textures by separately controlling global and local textural features through the primitive, grain, and point configuration (PGPC) texture model, a mathemati
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Zhang, Ya, Chunyi Chen, Xiaojuan Hu, Ling Li, and Hailan Li. "Saliency detection of textured 3D models based on multi-view information and texel descriptor." PeerJ Computer Science 9 (October 25, 2023): e1584. http://dx.doi.org/10.7717/peerj-cs.1584.

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Saliency-driven mesh simplification methods have shown promising results in maintaining visual detail, but effective simplification requires accurate 3D saliency maps. The conventional mesh saliency detection method may not capture salient regions in 3D models with texture. To address this issue, we propose a novel saliency detection method that fuses saliency maps from multi-view projections of textured models. Specifically, we introduce a texel descriptor that combines local convexity and chromatic aberration to capture texel saliency at multiple scales. Furthermore, we created a novel datas
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Appadurai, Jothi Prabha, and Bhargavi R. "Eye Movement Feature Set and Predictive Model for Dyslexia." International Journal of Cognitive Informatics and Natural Intelligence 15, no. 4 (2021): 1–22. http://dx.doi.org/10.4018/ijcini.20211001.oa28.

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Dyslexia is a learning disorder that can cause difficulties in reading or writing. Dyslexia is not a visual problem but many dyslexics have impaired magnocellular system which causes poor eye control. Eye-trackers are used to track eye movements. This research work proposes a set of significant eye movement features that are used to build a predictive model for dyslexia. Fixation and saccade eye events are detected using the dispersion-threshold and velocity-threshold algorithms. Various machine learning models are experimented. Validation is done on 185 subjects using 10-fold cross-validation
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Romaniuk, Vladimir R. "Method for predicting eye movement activity based on intelligent data analysis from a mobile portable electroencephalograph." Analysis and data processing systems, no. 3 (December 26, 2024): 77–89. https://doi.org/10.17212/2782-2001-2024-3-77-89.

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Eye movement processes, such as fixations and saccades, play a crucial role in human cognitive activity as they are closely associated with functions such as perception, attention, and decision-making. These processes are actively applied in various fields, including human-computer interaction systems and neurophysiological research. Modern eye-tracking methods based on optical systems provide high accuracy but have several significant limitations. In this regard, the use of electroencephalographic (EEG) data for analyzing eye movement activity is becoming a promising direction, as EEG provide
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Cornia, Marcella, Lorenzo Baraldi, Giuseppe Serra, and Rita Cucchiara. "Predicting Human Eye Fixations via an LSTM-Based Saliency Attentive Model." IEEE Transactions on Image Processing 27, no. 10 (2018): 5142–54. http://dx.doi.org/10.1109/tip.2018.2851672.

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Deng, Shuwen, David R. Reich, Paul Prasse, Patrick Haller, Tobias Scheffer, and Lena A. Jäger. "Eyettention: An Attention-based Dual-Sequence Model for Predicting Human Scanpaths during Reading." Proceedings of the ACM on Human-Computer Interaction 7, ETRA (2023): 1–24. http://dx.doi.org/10.1145/3591131.

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Eye movements during reading offer insights into both the reader's cognitive processes and the characteristics of the text that is being read. Hence, the analysis of scanpaths in reading have attracted increasing attention across fields, ranging from cognitive science over linguistics to computer science. In particular, eye-tracking-while-reading data has been argued to bear the potential to make machine-learning-based language models exhibit a more human-like linguistic behavior. However, one of the main challenges in modeling human scanpaths in reading is their dual-sequence nature: the word
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Zhang, Kaiwei, Dandan Zhu, Xiongkuo Min, and Guangtao Zhai. "Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 9 (2025): 9977–84. https://doi.org/10.1609/aaai.v39i9.33082.

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Textured meshes significantly enhance the realism and detail of objects by mapping intricate texture details onto the geometric structure of 3D models. This advancement is valuable across various applications, including entertainment, education, and industry. While traditional mesh saliency studies focus on non-textured meshes, our work explores the complexities introduced by detailed texture patterns. We present a new dataset for textured mesh saliency, created through an innovative eye-tracking experiment in a six degrees of freedom (6-DOF) VR environment. This dataset addresses the limitati
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Wang, Yongxiang, William Clifford, Charles Markham, and Catherine Deegan. "Examination of Driver Visual and Cognitive Responses to Billboard Elicited Passive Distraction Using Eye-Fixation Related Potential." Sensors 21, no. 4 (2021): 1471. http://dx.doi.org/10.3390/s21041471.

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Distractions external to a vehicle contribute to visual attention diversion that may cause traffic accidents. As a low-cost and efficient advertising solution, billboards are widely installed on side of the road, especially the motorway. However, the effect of billboards on driver distraction, eye gaze, and cognition has not been fully investigated. This study utilises a customised driving simulator and synchronised electroencephalography (EEG) and eye tracking system to investigate the cognitive processes relating to the processing of driver visual information. A distinction is made between e
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Hsieh, Chihcheng, André Luís, José Neves, et al. "EyeXNet: Enhancing Abnormality Detection and Diagnosis via Eye-Tracking and X-ray Fusion." Machine Learning and Knowledge Extraction 6, no. 2 (2024): 1055–71. http://dx.doi.org/10.3390/make6020048.

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Integrating eye gaze data with chest X-ray images in deep learning (DL) has led to contradictory conclusions in the literature. Some authors assert that eye gaze data can enhance prediction accuracy, while others consider eye tracking irrelevant for predictive tasks. We argue that this disagreement lies in how researchers process eye-tracking data as most remain agnostic to the human component and apply the data directly to DL models without proper preprocessing. We present EyeXNet, a multimodal DL architecture that combines images and radiologists’ fixation masks to predict abnormality locati
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Schoonveld, W., and M. P. Eckstein. "A likelihood based metric to compare human and model eye movement fixations during visual search." Journal of Vision 8, no. 6 (2010): 379. http://dx.doi.org/10.1167/8.6.379.

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Conference papers on the topic "Human eye fixations; textured model"

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Glukhov, D. V., A. G. Merkulova, and S. A. Kalinina. "ADVANCED TECHNOLOGIES FOR ASSESSING THE STATE OF THE HUMAN-OPERATOR IN THE PROCESS OF PROFESSIONAL ACTIVITY." In The 16th «OCCUPATION and HEALTH» Russian National Congress with International Participation (OHRNC-2021). FSBSI “IRIOH”, 2021. http://dx.doi.org/10.31089/978-5-6042929-2-1-2021-1-136-140.

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Abstract: Introduction. The search for non-contact methods for assessing the functional state of a human operator in the process of professional activity is an urgent task of applied physiology. The technology for recording and analyzing physiological information based on the parameters of a person's voice can become one of the reliable and valid assessment methods. Research objective. Investigation of the possibility of non-contact voice biometrics for assessing fatigue, fatigue and / or psycho-emotional stress among operators in the course of their professional activities. Materials and meth
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