Visual Video Research Articles

Reliability of an Inertial Measurement System Applied to the Technical Assessment of Forehand and Serve in Amateur Tennis Players.

Traditional methods for evaluating tennis technique, such as visual observation and video analysis, are often subjective and time consuming. On the other hand, a quick and accurate assessment can provide immediate feedback to players and contribute to technical development, particularly in less experienced athletes. This study aims to validate the use of a single inertial measurement system to assess some relevant technical parameters of amateur players. Among other things, we attempt to search for significant correlations between the flexion extension and torsion of the torso and the lateral distance of the ball from the body at the instant of impact. This research involved a group of amateur players who performed a series of standardized gestures (forehands and serves) wearing a sensorized chest strap fitted with a wireless inertial unit. The collected data were processed to extract performance metrics. The percentage coefficient of variation for repeated measurements, Wilcoxon signed-rank test, and Spearman's correlation were used to determine the system's reliability. High reliability was found between sets of measurements in all of the investigated parameters. The statistical analysis showed moderate and strong correlations, suggesting possible applications in assessing and optimizing specific aspects of the technique, like the player's distance to the ball in the forehand or the toss in the serve. The significant variations in technical execution among the subjects emphasized the need for tailored interventions through personalized feedback. Furthermore, the system allows for the highlighting of specific areas where intervention can be achieved in order to improve gesture execution. These results prompt us to consider this system's effectiveness in developing an on-court mobile application.

Helping Rabbits Cope with Veterinary Acts and Vaccine-Related Stress: The Effects of the Rabbit Appeasing Pheromone (RAP).

Rabbits are subjected to challenges that induce stress and require them to continuously adapt. Veterinary procedures represent an important source of stress. In other pets, pheromone use was shown to help patients better cope with these procedures. This study aimed to evaluate whether continuous exposure to the rabbit appeasing pheromone (RAP) could help rabbits cope with the stress induced by routine clinical consultations and vaccinations. Twenty-four 5-week-old rabbits were housed in two identical rooms for 43 days, one in which the rabbits underwent continuous RAP treatment and one with the placebo. The rabbits were vaccinated 8 days afterwards, and their behaviour was evaluated using visual analogic scales (VASs) and videos. The rabbits were also examined seven times, on a weekly basis, using VASs to assess their behaviour. The video analysis showed that the RAP-treated rabbits were less inhibited (p = 0.03) and more in contact with the surgeon (p = 0.039) during vaccinations, while the non-treated rabbits kept their ears in the middle/flattened position (p = 0.003). The RAP-treated rabbits were also less agitated (VAS analysis, p = 0.02). During the consultations, a treatment × day effect was observed in favour of the RAP group for the rabbit state and rabbit reactivity VAS analysis (p < 0.0001). These findings seem to suggest that continuous RAP exposure could be a promising tool for helping rabbits cope with veterinary procedures.

Анализ отклонений дорожного покрытия при движении автономного транспортного средства

The main purpose of the study was to solve the problem of analyzing the road surface diversion in real time mode while driving an autonomous vehicle using machine vision combined with light line projection. The objects of the study were the machine vision video images and the subjects were the parameters and its processing algorithms. The results of assessing the deviation of the road surface from the horizontal level are shown based on processing of video images of the specific segments of a scale open-pit road model in laboratory conditions. For each specific segment, such as the beginnings and endings of longitudinal and transverse slopes, specific conditions by which the machine vision system processes changes in the geometry of the light line projections. The values of the perimeter and geometric shapes of the light line projection, as well as the values of their curvature and the degree of their pattern matching were used as the main parameters. The Shi-Tomasi angle detection algorithm was used to calculate the perimeter. A block diagram and a description of the software module functions are presented for analyzing the road surface diversion. The obtained results in the form of software and the underlying algorithms can be used to solve industrial problems concerned with controlling autonomous vehicles.

Optimalisasi Komersial Usaha Batik Al-Barokah Melalui Digital Marketing Dalam Menjaga Competitive Advantage

In the rapidly evolving era of digitalization in 2024, the batik business Al-Barokah has successfully increased its revenue through innovative digital marketing strategies. Through qualitative research with a case study approach, the use of social media platforms such as Facebook, Instagram, and WhatsApp has proven effective in disseminating information, creating positive perceptions, and expanding the market reach for batik products. Despite facing intense competition, Al-Barokah batik continues to innovate with unique product quality, utilizing website design features and visual videos to promote its products. With the right digital marketing approach, Al-Barokah has significantly increased its revenue in 2024, emphasizing the strategic role of digital marketing in enhancing competitiveness and sustainability in the current digital era.

Dental Adaptation Strategies for Children with Autism Spectrum Disorder-A Systematic Review of Randomized Trials.

Background: Children with Autism Spectrum Disorder (ASD) often struggle with dental care due to sensory sensitivities and behavioral issues, increasing their risk for oral health problems. Adaptation strategies such as visual aids, video modeling, and sensory-adapted environments aim to improve their dental experiences. Methods: A systematic review of randomized controlled trials (RCTs) was conducted according to PRISMA 2020 guidelines using the PubMed, Scopus, Embase, and Cochrane databases. Of the 1072 records screened, nine RCTs were included in the analysis. Studies included children with ASD under 18 years and compared dental adaptation techniques with traditional care. The risk of bias and study quality were assessed. The quality of evidence for the results was determined using the GRADE tool. Results: Nine RCTs with sample sizes ranging from 25 to 138 participants showed significant improvements in oral hygiene, reduced anxiety, and increased cooperation. Video modeling and sensory-adapted environments were particularly effective in lowering distress during dental visits. Conclusions: Dental adaptation strategies, especially video modeling and sensory-adapted environments, effectively improve oral health outcomes and reduce anxiety in children with ASD. More research is needed to explore the long-term effects and include children with severe ASD.

The Effect of Audio-Visual Learning Media on the Memory of Elementary School Students

This study aims to determine the effect of using audio-visual learning media on students' memory through the learning outcomes test. This research was conducted using an experimental method involving two classes, namely the experimental class and the control class. The results showed that the experimental class, which used learning media, had quite good learning outcomes after using audio visual, when compared to conventional classes that did not use audio visual learning media. Thus it can be concluded that the increase in learning outcomes in the experimental class shows that students have a good memory of the material they learn through audio visual learning videos. Future researchers are expected to further examine the use of audio-visual learning media from different perspectives.

Enhancing Video Anomaly Detection with Improved UNET and Cascade Sliding Window Technique

Computer vision video anomaly detection still needs to be improved, especially when identifying images with unusual motions or objects. Current approaches mainly concentrate on reconstruction and prediction methods, and unsupervised video anomaly detection faces difficulties because there are not enough tagged abnormalities, which reduces accuracy. This paper presents a novel framework called the Improved UNET (I-UNET), designed to counteract overfitting by addressing the need for complex models that can extract subtle information from video anomalies. Video frame noise can be eliminated by preprocessing the frames with a Weiner filter. Moreover, the system uses Convolution Long Short-Term Memory (ConvLSTM) layers to smoothly integrate temporal and spatial data into its encoder and decoder portions, improving the accuracy of anomaly identification. The Cascade Sliding Window Technique (CSWT) is used post-processing to identify anomalous frames and generate anomaly scores. Compared to baseline approaches, experimental results on the UCF, UCSDped1, and UCSDped2 datasets demonstrate notable performance gains, with 99% accuracy, 90.8% Area Under Curve (AUC), and 10.9% Equal Error Rate (EER). This study provides a robust and accurate framework for video anomaly detection with the highest accuracy rate.

Basketball player motion detection and motion mode analysis based on biomechanical sensors

Basketball player motion detection and analysis are crucial for optimizing performance and preventing injuries. Traditional methods often rely on visual observation and video analysis, lacking precision and real-time feedback. In this study, a unique novel Intelligent Bayesian tuned-augmented Support Vector Machine (IB-ASVM) was proposed for predicting basketball players’ motion modes and performance analysis using the biomechanical sensor data. Advancements in biomechanical sensors such as accelerometers, gyroscopes, and force sensors are deployed into ESP32 to build a player’s wearable gadget. This gadget provides dynamic players with real-time sensing data. Data are transmitted to the cloud via Wi-Fi 7.0 for motion analysis and this model is stimulated using Arduino IDE. The Kalman Filter reduces noise and smoothens sensor data such as acceleration, and angular velocity. Then, the filtered data is employed in the Discrete Wavelet Transform (DWT) to capture time-frequency characteristics of motion signals, making it ideal for extracting relevant features. The featured data are utilized in the ASVM model to classify and detect the motion modes of the basketball players via IB optimization. The Tensor Flow software is used to implement the IB-ASVM model. The result demonstrates that IB-ASVM most accurately predicts the jump shot, layup, dribbling, running, pivoting, passing, free throw, and motion states of the basketball players. The IB-ASVM model accurately classifies basketball motion states using biomechanical sensor data, enhancing performance optimization and injury prevention through precise motion detection.

Comparison of Macintosh laryngoscope and King Vision video laryngoscope for endotracheal intubation in adult patients

Background: Development of video laryngoscope has made management of airway easier. 0ur study was aimed to compare the efficacy of Macintosh laryngoscope and King Vision video laryngoscope for endotracheal intubation in adult patients under general anesthesia. Objectives: The primary objective of the study was to compare the glottic view obtained , the need for external manipulation, endotracheal tube insertion time and attempts taken for successful intubation with Macintosh laryngoscope and King Vision video laryngoscope. The secondary objective was to estimate the changes in hemodynamic parameters and to evaluate the occurrence of complications during intubation. Materials and Methods: The study included 136 patients posted for surgery under general anesthesia. Patients were randomly allocated in group C (N=68) and group V (N=68 ).Endotracheal intubation was done in group C by Macintosh and in group V by King Vision video laryngoscope. Laryngoscopy was assessed by Cormack Lehane grading and the need for any manipulation. The intubation time was calculated with each blade. Hemodynamic parameters were recorded and any complication during laryngoscopy and intubation were noted. The observations were analysed statistically by SPSS Program for windows version 28. Results: In group C, 61.8% of patients had Cormack and Lehane score I while in group V 76.5 % of patients had score I . Mean time of successful intubation was 34.90±8.35 sec in group C while in group V it was 32.82± 5.20 second . There was no statistical difference in distribution of patients according to number of attempts of intubation. In group C, 64.7% of patients needed external laryngeal pressure while in group V 97.1 % patients were intubated without external laryngeal pressure. Both the groups were comparable in relation to changes in hemodynamic parameters and any complications associated with laryngoscopy and intubation. Conclusion: We conclude that glottic view is better obtained with King Vision Video laryngoscope whereas optimisation of position and external laryngeal manipulation is often required with Macintosh laryngoscope to get similar glottic view. Introduction of King Vision video laryngoscope into the oral cavity takes time but intubation is easier with it. Hemodynamic variables and complications during the procedure are equally distributed between the two devices.

Video Visualization and Visual Analytics: A Task-Based and Application- Driven Investigation

Video Visualization and Visual Analytics: A Task-Based and Application- Driven Investigation

AUDIOVISUAL METHOD IN LEARNING FOREIGN LANGUAGES

The article reveals the essence of the audiovisual method of teaching foreign languages. The main methods of learning foreign languages are characterized (grammatical translation, audio-lingual, communicative, immersive, direct, suggestive, neurolinguistic methods). The history of the emergence of the audiovisual method is traced and the contribution of various scientists to its development is analyzed (P. Rivan, R. Lado, R. Riсher). It is noted that the audiovisual method of learning foreign languages is a teaching method based on a combination of auditory (audio) and visual (video) stimuli, i.e. the defining feature of the method is the simultaneous use of sound and image. The importance of the method in the context of further development of multimedia resources is emphasized. The main characteristics of the method are presented: combination of images and sounds, contextual learning, emphasis on listening comprehension and pronunciation, lack of translation, repeated practice. Determined components of the method: listening, watching videos, repetition, perception of context. Advantages and disadvantages of the method are outlined. The advantages of the audiovisual method include: improving perception and memorization, immersive learning, getting closer to the natural language environment, active use of the context, and gradual mastery of the language. The limitations of the audiovisual method are: less emphasis on writing, the need for technical resources, which can make it difficult to use the method in schools or at home. Prospects for further research of the audiovisual method and its potential are indicated, especially in the context of technology development and individualization of education. It was concluded that the audiovisual method is a powerful tool for the initial stage of language learning, but it needs to be supplemented with other methods for comprehensive language acquisition.

Comparative dimensions of COVID-19 visual health literacy: social media news imagery in Germany and China

The COVID-19 pandemic prompted governments worldwide to utilise social media news platforms for disseminating critical public health information and safety protocols. Visual aids, including photographs, videos, charts, and infographics, played a key role in conveying health-related messages. However, there are variations in visual communication practices across countries, influenced by local health communication habits and cultural contexts. This study examines these variations in the visual health discourse that emerged in China and Germany during the pandemic, focusing on metaphorical mapping as a central analytical tool. We introduce the concept of “visual dataset fingerprints,” outlining the distinct composition of public health visuals on eight social news media platforms in Germany and China. Our descriptive analysis encompasses over 3700 digital visual media posts related to COVID-19, shared by leading national news media accounts in German, English, and Mandarin on microblogs in 2022. As a preliminary outcome of our study, we observe differences in image use based on the analysis of 1678 media posts by four Chinese outlets and 1329 media posts by four German outlets. These differences may reflect variations in how public opinion, perceptions, and attitudes toward COVID-19 policies are shaped across languages and cultures. Through its comparative visual analysis, our pilot study offers the potential for a new research approach to global healthcare communication in social news media and digital visual cultures.

Visual rigid laryngoscopy versus video laryngoscopy for endotracheal intubation in elderly patients: A randomized controlled trial.

To assess the efficacy and safety of visual rigid laryngoscopy and video laryngoscopy and to provide clinical information for developing a more suitable intubation tool for elderly patients. In 75 consecutive elderly patients undergoing elective surgery in a single institution, tracheal intubation was randomly performed by 2 experienced anaesthesiologists using visual rigid laryngoscopy (Group I, n = 38) or video laryngoscopy (Group II, n = 37). The primary outcome was intubation time. Secondary outcomes were the first-attempt success rate of tracheal intubation, haemodynamic responses at 1, 3, and 5 min after intubation and the incidence of postoperative airway complications, including immediate complications and postoperative complaints. The intubation times were 35.0 (30.0-41.5) s and 42.5 (38.0-51.3) s in Groups I and II, respectively (P < 0.001). The difference in direct complications between the two groups was statistically significant (P < 0.05). In contrast, there was no significant difference between the two groups regarding the follow-up of the main complaint 30 min and 24 h after tracheal extubation (P > 0.05). There was no difference in the intubation success rate between the 2 groups (P > 0.05). The haemodynamic responses at 1, 3, and 5 min after intubation were not significantly different (P > 0.05). Compared with that of video laryngoscopy, the intubation time of visual rigid laryngoscopy in elderly patients was shorter. At the same time, visual rigid laryngoscopy reduced the incidence of immediate complications. However, during endotracheal intubation, there was no significant difference in haemodynamics between the two groups. ChiCTR2100054174.

Dynamic assessment of visual fatigue during video watching: Validation of dynamic rating based on post-task ratings and video features

People watching video displays for long durations experience visual fatigue and other symptoms associated with visual discomfort. Fatigue-reduction techniques are often applied but may potentially degrade the immersive experience. To appropriately adjust fatigue-reduction techniques, the changes in visual fatigue over time should be analyzed which is crucial for the appropriate adjustment of fatigue-reduction techniques. However, conventional methods used for assessing visual fatigue are inadequate because they rely entirely on post-task surveys, which cannot easily determine dynamic changes. This study employed a dynamic assessment method for evaluating visual fatigue in real-time. Using a joystick, participants continuously evaluated subjective fatigue whenever they perceived changes. A Simulator Sickness Questionnaire (SSQ) validated the results, which indicated significant correlations between dynamic assessments and the SSQ across five items associated with symptoms associated with visual discomfort. Furthermore, we explored the potential relationship between dynamic visual fatigue and objective video features, e.g., optical flow and the V-values of the hue/saturation value (HSV) color space, which represent the motion and brightness of the video. The results revealed that dynamic visual fatigue significantly correlated with both the optical flow and the V-value. Moreover, based on machine learning models, we determined that the changes in visual fatigue can be predicted based on the optical flow and V-value. Overall, the results validate that dynamic assessment methods can form a reliable baseline for real-time prediction of visual fatigue.

Real-Time Internet-based Technology Applying Machine Learning Algorithm to Identify Airplane

Aircraft identification is critical in remote sensing for both civil and military purposes. The main challenge arises from subtle characteristics that cause significant variation within the same segment, such as differences in size, posture and angle. , while only minor differences exist. Among similar subcategories, it is important to accurately identify aircraft types such as radar systems, although commonly used, and often lacking accuracy. Anaconda, a state-of-the-art object recognition algorithm for aircraft recognition in the environment, achieves 98% training accuracy and 75% artificial intelligence accuracy by allowing computer systems to recognize objects from visual images or videos. Allows for analysis. The system is further equipped with an audio alert feature that activates when a potentially dangerous aircraft is detected. The project uses Python 3.6 (or later) and the necessary Python modules is, which makes it efficient and effective

Analisis Pemanfaatan AI dalam Komunikais Visual pada Akun Tiktok @ainusantara

This article focuses on TikTok social media that uses AI (Artificial intelligence) technology to visualize video content. In this day and age, technology is increasingly sophisticated, one of which is AI technology which plays a major role in creating content in a short time. One of the unique concepts of using AI (artificial intelligence) is the balance to attractively visualize each object in the image. This technology can also edit and create content in the form of videos, images, illustrations, etc. The use of AI in visual communication in video content has a great effect on creating visual aesthetics to be more beautiful and have real color contrasts, and can also provide information with the video without having to use words. This research will also look at the technical description of how AI (Artificial Intelligence) can provide great benefits in providing information through video visualization. To achieve this goal, the researcher uses a qualitative approach method with phenomenology in order to get a comprehensive picture of the object of research. The role of AI in visual communication is expected to provide great benefits and apply it properly through creativity and innovation that comes from human ideas to create interesting images or videos.

MapGPT: an autonomous framework for mapping by integrating large language model and cartographic tools

ABSTRACT The mapping process generally involves intricate operations, such as symbol design, layout design, and text annotation, demanding a high level of professional expertise. The high requirement for map producers hinders the promotion and widespread adoption of mapping. Consequently, researchers are concentrating on techniques to automate and enhance the intelligence of the mapping process. For example, some studies attempt to train deep learning models for mapping, including methods like map style transfer. However, these approaches typically treat the entire map as a global input and generate a new map as output, lacking the flexibility to consider and control detailed elements within a map. Therefore, in this paper, we propose a large language model-based intelligent mapping framework, termed MapGPT, which can be used for mapping by considering the map as an integration of various map elements. Specifically, multiple professional mapping tools are designed in MapGPT, and each tool is designed to control a corresponding map element. With these tools, a large language model is used to first understand the demand of users based on mere natural language descriptions, and subsequently automatically invoke appropriate tools in sequence to generate a map. Furthermore, by utilizing a memory component to store interaction information, users can interact with MapGPT through conversation to adjust map elements such as color and position. In conclusion, MapGPT offers user-friendly mapping experience, showing potential to be a mapping assistant for professional map producers. A comprehensive demonstration of this framework is provided in a visual case study video, accessible at https://github.com/AGI-GIS/MapGPT.

Deep learning-powered visual place recognition for enhanced mobile multimedia communication in autonomous transport systems

The progress of autonomous transport systems (ATS) involves efficient multimedia communication for real-time data tradeoffs and environmental issues. Deep learning (DL) powered visual place recognition (VPR) was developed as an effective tool to improve mobile multimedia communication in ATS. VPR relates to the capability of a method or device to recognize and identify particular places or locations from the visual scene. This procedure involves inspecting visual data, like images or video frames, to control the unique features or features connected with diverse locations. By leveraging camera sensors, VPR allows vehicles to detect their surroundings, enabling context-aware communication and enhancing the entire system's performance. DL-empowered VPR offers a transformative manner to improve mobile multimedia communication in ATS. By identifying and understanding their situation, autonomous vehicles can communicate most effectively and operate reliably and safely, paving the way for a future characterized by seamless and intelligent transportation. This article develops a novel Deep Learning-Powered Visual Place Recognition for Enhanced Multimedia Communication in Autonomous Transport Systems (DLVPR-MCATS) methodology. The main aim of the DLVPR-MCATS methodology is to recognize visual places or not utilize optimal DL approaches. For this purpose, the DLVPR-MCATS approach utilizes a bilateral filtering (BF) based preprocessing model. For the feature fusion model, the DLVPR-MCATS approach follows three models: residual network (ResNet), EfficientNet, and MobileNetv2. Moreover, the hyperparameter tuning method uses the Harris Hawks Optimization (HHO) model. Finally, the bidirectional long short-term memory (BiLSTM) technique is implemented to recognize visual places. A wide range of simulations is executed to validate the solution of the DLVPR-MCATS method. The experimental validation of the DLVPR-MCATS method portrayed a superior performance over other models concerning various aspects.

Distinct and additive effects of visual and vibratory feedback for motor rehabilitation: an EEG study in healthy subjects

IntroductionThe use of visual and proprioceptive feedback is a key property of motor rehabilitation techniques. This feedback can be used alone, for example, for vision in mirror or video therapy, for proprioception in focal tendon vibration therapy, or in combination, for example, in robot-assisted training. This Electroencephalographic (EEG) study in healthy subjects explored the distinct neurophysiological impact of adding visual (video therapy), proprioceptive (focal tendinous vibration), or combined feedback (video therapy and focal tendinous vibration) to a motor imagery task.MethodsSixteen healthy volunteers performed 20 mental imagery (MI) tasks involving right wrist extension and flexion under four conditions: MI alone (IA), MI + video feedback observation (IO), MI + vibratory feedback (IV), and MI + observation + vibratory feedback (IOV). Brain activity was monitored with EEG, and time-frequency neurophysiological markers of movement were computed. The emotions of the patients were also measured during the task.ResultsIn the alpha band, we observed bilateral ERD in the visual feedback conditions (IO, IOV). In the beta band, the ERD was bilateral in the IA, IV and IOV but more lateralized in the IV and IOV. After movement, we observed strong ERS in the IO and IOV but not in the IA or IV. Embodiment was stronger in conditions with vibratory feedback (IOV > IV > IA and IO)ConclusionConditions with visual feedback (IO, IOV) recruit the mirror neurons system (alpha ERD) and provide more accurate feedback of the task than IA and IV, which triggers motor validation pathways (beta rebound analysis). Vibratory feedback enhances the recruitment of the left sensorimotor areas, with a synergistic effect in the IOV (beta ERD analysis), thus maximizing embodiment. Visual and vibratory feedback recruits the sensorimotor cortex during motor imagery in different ways and can be combined to maximize the benefits of both techniquesTrial registrationhttps://clinicaltrials.gov/study/NCT04449328.

ANALYSIS VIDEO BASED LEARNING DESIGN IN PRACTICE COURSE AT VOCATIONAL SCHOOL

This study aims to design educational videos as video-based learning and determine the design that makes students more interested in paying attention to the distance learning process. If students want to pay attention to the material during the learning process, students will also get the maximum learning experience. The study was focused on the Department of Fashion at SMKN 1 Dawuan Subang to improve clarity. To obtain empirical data, this study used quantitative comparative with data collection using questionnaires with census sampling. The number of respondents is 22 students. The steps are input measurement design video with Bandicam and output measurement obtained from the evaluation results based on three elements for video design and implementation: cognitive load, student engagement, and active learning together. The data collection technique used a questionnaire. The results indicate that video-based learning using Bandicam was most effective in organizing tempo, but more attention must be paid to segmentation because the visualization video was formal and tended to be static. Further research should explore video-based learning using more engaging and dynamic applications like Prezi or similar tools.