Human Reading Knowledge Inspired Text Line Extraction

Wang, Liuan; Uchida, Seiichi; Zhu, Anna; Sun, Jun

doi:10.1007/s12559-017-9490-4

Cited by 6 publications

(5 citation statements)

References 30 publications

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“…With a similar focus on environmental constraints, Wang and colleagues [28] suggest that humans use a model-based predictive approach to anticipate the physical dynamics of the environment and plan a movement. Researchers have also generated smooth movement trajectories for agents using optimization algorithms such as particle swarm [29].…”

Section: Introductionmentioning

confidence: 99%

Information Theoretic Model to Simulate Agent-Signage Interaction for Wayfinding

et al. 2019

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Signage systems are critical for communicating spatial information during wayfinding among a plethora of noise in the environment. A proper signage system can improve wayfinding performance and user experience by reducing the perceived complexity of the environment. However, previous models of sign-based wayfinding do not incorporate realistic noise or quantify the reduction in perceived complexity from the use of signage. Drawing upon concepts from information theory, we propose and validate a new agent-signage interaction model that quantifies available wayfinding information from signs for wayfinding. We conducted two online crowd-sourcing experiments to compute the distribution of a sign's visibility and an agent's decision-making confidence as a function of observation angle and viewing distance. We then validated this model using a virtual reality (VR) experiment with trajectories from human participants. The crowd-sourcing experiments provided a distribution of decision-making entropy (conditioned on visibility) that can be applied to any sign/environment. From the VR experiment, a training dataset of 30 trajectories was used to refine our model, and the remaining test dataset of 10 trajectories was compared with agent behavior using dynamic time warping (DTW) distance. The results revealed a reduction of 38.76% in DTW distance between the average trajectories before and after refinement. Our refined agentsignage interaction model provides realistic predictions of human wayfinding behavior using signs. These findings represent a first step towards modeling human wayfinding behavior in complex real environments in a manner that can incorporate several additional random variables (e.g., environment layout). Keywords Cognitive agent • Information theory • Entropy • Artificial intelligence • Agent-based model • Signage system Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Section: Introductionmentioning

confidence: 99%

Information Theoretic Model to Simulate Agent-Signage Interaction for Wayfinding

et al. 2019

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“…To this aim, we proposed and evaluated a set of tasks (drawings, handwriting in cursive/capital letters, and signature) and categories of tasks (cognitive, mechanical, and fine motor tasks). Future research will explore a range of innovative, cognitively inspired approaches for contextual unimodal and multimodal processing [36][37][38][39][40][41][42].…”

Section: Discussionmentioning

confidence: 99%

On the Handwriting Tasks’ Analysis to Detect Fatigue

Garnacho-Castaño¹,

Faundez-Zanuy²,

Lopez-Xarbau³

2020

Applied Sciences

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Practical determination of physical recovery after intense exercise is a challenging topic that must include mechanical aspects as well as cognitive ones because most of physical sport activities, as well as professional activities (including brain–computer interface-operated systems), require good shape in both of them. This paper presents a new online handwritten database of 20 healthy subjects. The main goal was to study the influence of several physical exercise stimuli in different handwritten tasks and to evaluate the recovery after strenuous exercise. To this aim, they performed different handwritten tasks before and after physical exercise as well as other measurements such as metabolic and mechanical fatigue assessment. Experimental results showed that although a fast mechanical recovery happens and can be measured by lactate concentrations and mechanical fatigue, this is not the case when cognitive effort is required. Handwriting analysis revealed that statistical differences exist on handwriting performance even after lactate concentration and mechanical assessment recovery. This points out a necessity of more recovering time in sport and professional activities than those measured in classic ways.

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“…Precision is calculated as the proportion of true positives to complete detection. Precision can be expressed mathematically (2). As shown in Table 3, the precision effectiveness of the proposed approach is considerably higher than that of the existing method of text extraction for small-sized textual images.…”

Section: Precisionmentioning

confidence: 98%

“…Complex videos and complex image text messages produce quality, just like text messages in images are used in many complex image learning [2][3][4] and indulging implementation processes, including language translators, book digitisation, video or image recovery [2]. Considerable devotion has been paid recently to the use of pre-programmed text detection and text recognition [5].…”

Section: Introductionmentioning

confidence: 99%