Automatic detection, tracking and counting of birds in marine video content

Robust automatic detection of moving objects in a marine context is a multi-faceted problem due to the complexity of the observed scene. The dynamic nature of the sea caused by waves, boat wakes, and weather conditions poses huge challenges for the development of a stable background model. Moreover, camera motion, reflections, lightning and illumination changes may contribute to false detections. Dynamic background subtraction (DBGS) is widely considered as a solution to tackle this issue in the scope of vessel detection for maritime traffic analysis. In this paper, the DBGS techniques suggested for ships are investigated and optimized for the monitoring and tracking of birds in marine video content. In addition to background subtraction, foreground candidates are filtered by a classifier based on their feature descriptors in order to remove non-bird objects. Different types of classifiers have been evaluated and results on a ground truth labeled dataset of challenging video fragments show similar levels of precision and recall of about 95% for the best performing classifier. The remaining foreground items are counted and birds are tracked along the video sequence using spatio-temporal motion prediction. This allows marine scientists to study the presence and behavior of birds

Developing a Critical Discourse About Teaching and Learning: The Case of a Secondary Science Video Club

Video is used widely to support teachers’ learning and enactment of responsive instruction. Informed by principles of video club design, we designed a video club to support secondary science teachers developing a vision of responsive teaching, attention to student thinking, and a critical discourse to analyze their own and others’ efforts to enact responsive practices. In this study, we investigate if and how teachers developed a critical discourse in this context. Analysis reveals that the group developed a more collaborative, interpretive, and evidence-based discourse about teaching and learning. These findings contribute to research on video clubs as a professional development model to support teacher learning, as well as make visible how teachers shifted to develop a more critical lens for discussing teaching and learning. This study has implications for designing professional learning that will result in sustained, generative development in the context of instructional reform

Teacher learning in the context of Lesson Study: A video-based analysis of teacher discussions

This paper contributes to our understanding of teacher learning in the context of Lesson Study (LS), a model of professional development that involves collaborative lesson planning and evaluation. Video-recorded LS discussions of mathematics teachers based in London were analysed for this purpose. Two inter-related studies are presented: the first involved the construction of a reliable coding protocol for video analysis; the second used this protocol for coding 120 fragments of discussions amongst 91 teachers. Findings are discussed with reference to tests of reliability and results of multilevel analysis, which reveal differential effects of particular forms of interactions on learning processes.This research was made possible through a grant of the London School Excellence Fund

Develop a Video Tutorial on Basic Sepak Badek Techniques in Sepak Takraw for Physical Education Students in the 2021/2022 Academic Year

Objective. The rapid advancement of technology has led to significant innovations in various fields, including education. Educators are expected to leverage these technological developments to design new and effective learning strategies for their students. This study focuses on the development of video tutorial-based learning media that employs the ADDIE model to teach basic football sila techniques in the context of the sepak takraw game. This learning product is specifically designed for students enrolled in the Penjaskesrek study program. Material and Methods. The ADDIE development model is a well-known instructional design approach that consists of five key stages; analysis, design, development, implementation, and evaluation. For the purpose of this research, a score scale questionnaire was utilized as the data collection instrument. Result.  According to the research findings, the teaching materials were well-received in terms of their content, with a 93.33% rating. The learning media element was also highly rated, with a score of 93.33%. Similarly, the learning design part received a very good rating of 96.25%. The field practitioner aspect of the materials also received a good rating of 92.00%. During individual product trials, the criteria received a rating of 91.10%, while small-group product trials received a rating of 94.66%. Conclusion. The study concluded that the instructional materials for learning basic sepak takraw techniques, which were based on video tutorials, were found to be both feasible and effective for Penjaskesrek study program students. The research indicates that these materials can be incorporated into the curriculum to enhance the learning experience of students in the fields of physical education, sports, and health. Overall, the findings suggest that utilizing video tutorials as a form of instructional media can be a valuable tool in facilitating the acquisition of fundamental skills in sepak takraw.Objective. The rapid advancement of technology has led to significant innovations in various fields, including education. Educators are expected to leverage these technological developments to design new and effective learning strategies for their students. This study focuses on the development of video tutorial-based learning media that employs the ADDIE model to teach basic football sila techniques in the context of the sepak takraw game. This learning product is specifically designed for students enrolled in the Penjaskesrek study program. Material and Methods. The ADDIE development model is a well-known instructional design approach that consists of five key stages; analysis, design, development, implementation, and evaluation. For the purpose of this research, a score scale questionnaire was utilized as the data collection instrument. Result.  According to the research findings, the teaching materials were well-received in terms of their content, with a 93.33% rating. The learning media element was also highly rated, with a score of 93.33%. Similarly, the learning design part received a very good rating of 96.25%. The field practitioner aspect of the materials also received a good rating of 92.00%. During individual product trials, the criteria received a rating of 91.10%, while small-group product trials received a rating of 94.66%. Conclusion. The study concluded that the instructional materials for learning basic sepak takraw techniques, which were based on video tutorials, were found to be both feasible and effective for Penjaskesrek study program students. The research indicates that these materials can be incorporated into the curriculum to enhance the learning experience of students in the fields of physical education, sports, and health. Overall, the findings suggest that utilizing video tutorials as a form of instructional media can be a valuable tool in facilitating the acquisition of fundamental skills in sepak takraw

COMPASS: A Formal Framework and Aggregate Dataset for Generalized Surgical Procedure Modeling

Purpose: We propose a formal framework for the modeling and segmentation of minimally-invasive surgical tasks using a unified set of motion primitives (MPs) to enable more objective labeling and the aggregation of different datasets. Methods: We model dry-lab surgical tasks as finite state machines, representing how the execution of MPs as the basic surgical actions results in the change of surgical context, which characterizes the physical interactions among tools and objects in the surgical environment. We develop methods for labeling surgical context based on video data and for automatic translation of context to MP labels. We then use our framework to create the COntext and Motion Primitive Aggregate Surgical Set (COMPASS), including six dry-lab surgical tasks from three publicly-available datasets (JIGSAWS, DESK, and ROSMA), with kinematic and video data and context and MP labels. Results: Our context labeling method achieves near-perfect agreement between consensus labels from crowd-sourcing and expert surgeons. Segmentation of tasks to MPs results in the creation of the COMPASS dataset that nearly triples the amount of data for modeling and analysis and enables the generation of separate transcripts for the left and right tools. Conclusion: The proposed framework results in high quality labeling of surgical data based on context and fine-grained MPs. Modeling surgical tasks with MPs enables the aggregation of different datasets and the separate analysis of left and right hands for bimanual coordination assessment. Our formal framework and aggregate dataset can support the development of explainable and multi-granularity models for improved surgical process analysis, skill assessment, error detection, and autonomy.Comment: 22 pages, 6 figures, 12 table

Video vehicle detection at signalised junctions: a simulation-based study

Many existing advanced methods of traffic signal control depend on information about approaching traffic provided by inductive loop detectors at particular points in the road. But analysis of images from CCTV cameras can in principle provide more comprehensive information about traffic approaching and passing through junctions, and cameras may be easier to install and maintain than loop detectors, and some systems based on video detection have already been in use for some time. Against this background, computer simulation has been used to explore the potential of existing and immediately foreseeable capability in automatic on-line image analysis to extract information relevant to signal control from images provided by cameras mounted in acceptable positions at signal-controlled junctions. Some consequences of extracting relevant information in different ways were investigated in the context of an existing detailed simulation model of vehicular traffic moving through junctions under traffic-responsive signal control, and the development of one basic and one advanced algorithm for traffic-responsive control. The work was confined as a first step to operation of one very simple signalcontrolled junction. Two techniques for extraction of information from images were modelled - a more ambitious technique based on distinguishing most of the individual vehicles visible to the camera, and a more modest technique requiring only that the presence of vehicles in any part of the image be distinguished from the background scene. In the latter case, statistical modelling was used to estimate the number of vehicles corresponding to any single area of the image that represents vehicles rather than background. At the simple modelled junction, each technique of extraction enabled each of the algorithms for traffic-responsive control of the signals to achieve average delays per vehicle appreciably lower than those given by System D control, and possibly competitive with those that MOVA would give, but comparison with MOVA was beyond the scope of the initial study. These results of simulation indicate that image analysis of CCTV pictures should be able to provide sufficient information in practice for traffic-responsive control that is competitive with existing techniques. Ways in which the work could be taken further were discussed with practitioners, but have not yet been progressed

A Bayesian hierarchy for robust gaze estimation in human–robot interaction

In this text, we present a probabilistic solution for robust gaze estimation in the context of human–robot interaction. Gaze estimation, in the sense of continuously assessing gaze direction of an interlocutor so as to determine his/her focus of visual attention, is important in several important computer vision applications, such as the development of non-intrusive gaze-tracking equipment for psychophysical experiments in neuroscience, specialised telecommunication devices, video surveillance, human–computer interfaces (HCI) and artificial cognitive systems for human–robot interaction (HRI), our application of interest. We have developed a robust solution based on a probabilistic approach that inherently deals with the uncertainty of sensor models, but also and in particular with uncertainty arising from distance, incomplete data and scene dynamics. This solution comprises a hierarchical formulation in the form of a mixture model that loosely follows how geometrical cues provided by facial features are believed to be used by the human perceptual system for gaze estimation. A quantitative analysis of the proposed framework's performance was undertaken through a thorough set of experimental sessions. Results show that the framework performs according to the difficult requirements of HRI applications, namely by exhibiting correctness, robustness and adaptiveness

Association of Motivational Climate With Addictive Behaviors Depending on Type of Sport in University Students: Structural Equation Analysis

This research study aims at contrasting a structural model of the associations between the alcohol consumption, tobacco dependence, and the problematic use of video games with motivational climate toward sport depending on the category of sports practiced in a sample of Physical Education university students. The sample consisted of 775 university students from the Autonomous Community of Andalusia (Spain), aged between 21 and 35 (22.22 ± 3.76) years. The instruments used were the Perceived Motivational Climate in Sport Questionnaire (PMCSQ-2), the Alcohol Use Disorders Identification Test (AUDIT), the Fagerström Test for Nicotine Dependence (FTND), and the Questionnaire of Experiences Related to Video Games (QERV) questionnaires. A path model that fitted properly in the multigroup analysis for both categories of sports was used, χ2 = 19.843; gl = 8; p = .011; comparative fit index (CFI) = 0.911; normed fit index (NFI) = 0.903; incremental fit index (IFI) = 0.912; root mean square error approximation (RMSEA) = 0.085. An inverse association was shown between task climate and tobacco consumption in individual sports, being weaker in collective sports. This association is not significant for collective sports, but it is for individual sports for ego climate. However, a positive association was found between ego climate and the use of video games in individual sports, not being significant in the case of collective sports. The importance of promoting motivational climates oriented toward tasks that are based on the practice of collective sports is established, because they could act as protective factors against the development of addictive behavior in university students.This research study has been supported by the Education Innovation Project PID 16-45, named “Implementation of digital resources in the classroom for the development of psychosocial and motivational factors in students of the degree in Primary Education with the speciality in Physical Education,” funded by the University of Granada. Education Innovation Project PIBD Advanced 470, named “Program of teaching intervention in students of the degree in primary education and early childhood education through the use of new technologies for the improvement of the psychosocial factors of the students,” funded by the University of Granada. Project I+D+I “DISPERSA,” with code number TIN2015-67149-C3-R, named “Design of Pervasive Games Based on Learning Experiences Sensitive to Context” funded by the Ministry of Economy and Competitiveness. Precompetitive Research Projects for Young Researchers (PPJI_B-05); Self-plan Research of the University of Granada

A New Approach for Quality Management in Pervasive Computing Environments

This paper provides an extension of MDA called Context-aware Quality Model Driven Architecture (CQ-MDA) which can be used for quality control in pervasive computing environments. The proposed CQ-MDA approach based on ContextualArchRQMM (Contextual ARCHitecture Quality Requirement MetaModel), being an extension to the MDA, allows for considering quality and resources-awareness while conducting the design process. The contributions of this paper are a meta-model for architecture quality control of context-aware applications and a model driven approach to separate architecture concerns from context and quality concerns and to configure reconfigurable software architectures of distributed systems. To demonstrate the utility of our approach, we use a videoconference system.Comment: 10 pages, 10 Figures, Oral Presentation in ECSA 201