SPACE-TIME GRAPH-BASED CONVOLUTIONAL NEURAL NETWORKS OF STUDY ON MOVEMENT RECOGNITION OF FOOTBALL PLAYERS

Behaviour recognition technology is an interdisciplinary technology, integrating many research achievements in computer vision, deep learning, pattern recognition and other fields. The key information of bone data on human behavior can not only accurately describe the motion posture of the human body in three-dimensional space, but also its rigid connection structure is robust to various external interference factors. However, the behavioral recognition algorithm is influenced by different factors such as background, light and environment, which is easy to lead to unstable recognition accuracy and limited application scenarios. To address this problem, in this paper, we propose a noise filtering algorithm based on data correlation and skeleton energy model filtering, construct a set of football player data sets, using the ST-GCN algorithm to train the skeleton characteristics of football players, and construct a behavior recognition system applied to football players. Finally, by comparing the accuracy of Deep LSTM, 2s-AGCN and the algorithm in this paper, the accuracy of TOP1 and TOP5 is 39.97% and 66.34%, respectively, which are significantly higher than the other two algorithms. It can realize the statistics of athletes and analyze the technical and tactical movements of players on the football field

Motion-based technology to support motor skills screening in developing children: A scoping review

Background. Acquiring motor skills is fundamental for children's development since it is linked to cognitive development. However, access to early detection of motor development delays is limited. Aim. This review explores the use and potential of motion-based technology (MBT) as a complement to support and increase access to motor screening in developing children. Methods. Six databases were searched following the PRISMA guidelines to search, select, and assess relevant works where MBT recognised the execution of children's motor skills. Results. 164 studies were analysed to understand the type of MBT used, the motor skills detected, the purpose of using MBT and the age group targeted. Conclusions. There is a gap in the literature aiming to integrate MBT in motor skills development screening and assessment processes. Depth sensors are the prevailing technology offering the largest detection range for children from age 2. Nonetheless, the motor skills detected by MBT represent about half of the motor skills usually observed to screen and assess motor development. Overall, research in this field is underexplored. The use of multimodal approaches, combining various motion-based sensors, may support professionals in the health domain and increase access to early detection programmes.Funding for open access charge: Universidad de Málaga / CBUA

Human Action Recognition and Monitoring in Ambient Assisted Living Environments

Population ageing is set to become one of the most significant challenges of the 21st century, with implications for almost all sectors of society. Especially in developed countries, governments should immediately implement policies and solutions to facilitate the needs of an increasingly older population. Ambient Intelligence (AmI) and in particular the area of Ambient Assisted Living (AAL) offer a feasible response, allowing the creation of human-centric smart environments that are sensitive and responsive to the needs and behaviours of the user. In such a scenario, understand what a human being is doing, if and how he/she is interacting with specific objects, or whether abnormal situations are occurring is critical. This thesis is focused on two related research areas of AAL: the development of innovative vision-based techniques for human action recognition and the remote monitoring of users behaviour in smart environments. The former topic is addressed through different approaches based on data extracted from RGB-D sensors. A first algorithm exploiting skeleton joints orientations is proposed. This approach is extended through a multi-modal strategy that includes the RGB channel to define a number of temporal images, capable of describing the time evolution of actions. Finally, the concept of template co-updating concerning action recognition is introduced. Indeed, exploiting different data categories (e.g., skeleton and RGB information) improve the effectiveness of template updating through co-updating techniques. The action recognition algorithms have been evaluated on CAD-60 and CAD-120, achieving results comparable with the state-of-the-art. Moreover, due to the lack of datasets including skeleton joints orientations, a new benchmark named Office Activity Dataset has been internally acquired and released. Regarding the second topic addressed, the goal is to provide a detailed implementation strategy concerning a generic Internet of Things monitoring platform that could be used for checking users' behaviour in AmI/AAL contexts

Accuracy of Hidden Markov Models in Identifying Alterations in Movement Patterns during Biceps-Curl Weight-Lifting Exercise

This paper presents a comparison of mathematical and cinematic motion analysis regarding the accuracy of the detection of alterations in the patterns of positional sequence during biceps-curl lifting exercise. Two different methods, one with and one without metric data from the environment, were used to identify the changes. Ten volunteers performed a standing biceps-curl exercise with additional loads. A smartphone recorded their movements in the sagittal plane, providing information on joints and barbell sequential position changes during each lift attempt. An analysis of variance revealed significant differences in joint position (p < 0.05) among executions with three different loads. Hidden Markov models were trained with data from the bi-dimensional coordinates of the joint positional sequence to identify meaningful alteration with load increment. Tests of agreement tests between the results provided by the models with the environmental measurements, as well as those from image coordinates, were performed. The results demonstrated that it is possible to efficiently detect changes in the patterns of positional sequence with and without the necessity of measurement and/or environmental control, reaching an agreement of 86% between each other, and 100% and 86% for each respective method to the results of ANOVA. The method developed in this study illustrates the viability of smartphone camera use for identifying positional adjustments due to the inability to control limbs in an adequate range of motion with increasing load during a lifting task.info:eu-repo/semantics/publishedVersio

Interactive exploration of historic information via gesture recognition

Developers of interactive exhibits often struggle to �nd appropriate input devices that enable intuitive control, permitting the visitors to engage e�ectively with the content. Recently motion sensing input devices like the Microsoft Kinect or Panasonic D-Imager have become available enabling gesture based control of computer systems. These devices present an attractive input device for exhibits since the user can interact with their hands and they are not required to physically touch any part of the system. In this thesis we investigate techniques to enable the raw data coming from these types of devices to be used to control an interactive exhibit. Object recognition and tracking techniques are used to analyse the user's hand where movement and clicks are processed. To show the e�ectiveness of the techniques the gesture system is used to control an interactive system designed to inform the public about iconic buildings in the centre of Norwich, UK. We evaluate two methods of making selections in the test environment. At the time of experimentation the technologies were relatively new to the image processing environment. As a result of the research presented in this thesis, the techniques and methods used have been detailed and published [3] at the VSMM (Virtual Systems and Multimedia 2012) conference with the intention of further forwarding the area