Current Issue : April-June Volume : 2023 Issue Number : 2 Articles : 5 Articles
This paper presents the modified HEVC Screen Content Coding (SCC) that was adapted to be more efficient as an internal video coding of the MPEG Immersive Video (MIV) codec. The basic, unmodified SCC is already known to be useful in such an application. However, in this paper, we propose three additional improvements to SCC to increase the efficiency of immersive video coding. First, we analyze using the quarter-pel accuracy in the intra block copy technique to provide a more effective search of the best candidate block to be copied in the encoding process. The second proposal is the use of tiles to allow inter-view prediction inside MIV atlases. The last proposed improvement is the addition of the MIV bitstream parser in the HEVC encoder that enables selecting the most efficient coding configuration depending on the type of currently encoded data. The experimental results show that the proposal increases the compression efficiency for natural content sequences by almost 7% and simultaneously decreases the computational time of encoding by more than 15%, making the proposal very valuable for further research on immersive video coding....
In the last few years, the spreading of new technologies, such as augmented reality (AR), has been changing our way of life. Notably, AR technologies have different applications in the cultural heritage realm, improving available information for a user while visiting museums, art exhibits, or generally a city. Moreover, the spread of new and more powerful mobile devices jointly with virtual reality (VR) visors contributes to the spread of AR in cultural heritage. This work presents an augmented reality mobile system based on content-based image analysis techniques and linked open data to improve user knowledge about cultural heritage. In particular, we explore the uses of traditional feature extraction methods and a new way to extract them employing deep learning techniques. Furthermore, we conduct a rigorous experimental analysis to recognize the best method to extract accurate multimedia features for cultural heritage analysis. Eventually, experiments show that our approach achieves good results with respect to different standard measures....
At this stage, the most important content of rural construction includes the construction of rural public space, which is related to the environment of all rural areas, the happiness of villagers, and the inheritance and development of rural areas. Especially under the guidance of the rural revitalization strategy, the necessity of public space environment construction has become increasingly prominent, becoming an irreplaceable core content in rural construction. Therefore, we must closely focus on the development needs of rural areas at this stage, dig deep into the development of the public space environment, find corresponding design strategies, and maximize the completion of the real construction of beautiful rural areas. Rural public spaces have experienced the pain of new urbanization and rural intelligence. The most important public spaces in traditional agricultural societies, such as deep-water wells, trees, and sundecks, will slowly decline and fade. In the future, public space in rural areas must function in urban areas. Rural public spaces with complex roles and diverse types of public activities are the main orientations for the transformation of rural spaces in the future....
With the rapid development of the Internet, network media, as a new form of information dissemination, has penetrated into people’s daily life. In recent years, with the rapid transformation of Chinese social structure and the rise of self-media platforms, various social contradictions have been highlighted in the form of online public opinion. Especially on online multimedia platforms, the spread of online public opinion is more rapid, which can easily lead to social hotspots. In order to effectively supervise the public opinion information on the Internet, it is necessary to identify the target of the information on the multimedia platform and effectively screen the information, so as to control the network public opinion in the development stage. Aiming at the above problems, we propose a multitarget retrieval method based on a convolutional neural network, which uses multitarget detection algorithm to locate multitarget regions and extract regional features and uses cosine distance as a similarity measure for multitarget recognition. In view of the slow feature extraction speed of VGG model, a lightweight mobile network model is proposed to replace the original VGG model on the mobile phone to reduce the retrieval time and realize the recognition of specific targets on the multimedia platform, and it is applied to the verification of image recognition on the multimedia platform. The results show that the algorithm proposed in this paper has great advantages in multitarget recognition tasks....
With the development and progress of society, great changes have taken place in educational concepts and teaching models compared with the past. Faced with the new educational concept of advocating diversified teaching modes and all-round talent training, the teaching space under the traditional single-fixed teaching mode is insufficient.The field of digital media education is a form of education with the development of information technology. The purpose of this paper is to find out the construction form of teaching space under the new educational concept that adapts to the development of the social era and to respond to the constantly updated and emerging educational concept and teaching mode. The process is as follows: based on the collected education data, mining the specific factors that will affect the application ability of teachers’ digital education resources and building a multiple machine learning regression model using these objective and significant features to predict the score of teachers’ digital education resources application ability. Through the comparison and optimization of model performance, a more suitable prediction method was found. MSE, MAE, RMSE, and MAPE are used as performance evaluation indicators to compare the performance of each model. It is found that there are multilayer linear regression < mild gradient advance < extreme gradient advance < random forest in each indicator. In addition, in the two integration models, bagging idea represented by the random forest is more suitable for this group than two gradient boosting....
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