International Journal of Arts and Technology (21 papers in press)
Image classification of art works based on multiple naive Bayes algorithm
by Gang Liang
Abstract: In order to overcome the problems of unreasonable contrast and low classification accuracy in traditional art image classification, this paper proposes a new art image classification method based on multiple naive Bayes algorithm. This method uses image smoothing method to remove the noise of art works image and realise image preprocessing, constructs colour histogram to quantify the hue value of art works image to complete image feature extraction, obtains image feature points through multiple naive Bayes, obtains the generated feature descriptor of art works image, and realises the classification of art works image. The experimental results show that the classification accuracy of this method is as high as 99.6%, the image classification contrast is always in the best value, and the classification time is short.
Keywords: multiple naive Bayes algorithm; art works; image classification; image smoothing method; feature extraction; image feature descriptor.
Evaluation Analysis of Music based on Directed Weighted Complex Network and Statistics
by Xinyan Ma, Xinyu Zhou, Tingting Mo
Abstract: Music is influential, previously creative music has a certain degree of influence on new music and artists. The influence can be measured by the similarity of musical characteristics. For this feature, a complex network model is established by using knowledge of graph theory, cluster analysis, etc. Based on data mining and analysis, trends of development in artists and genres are examined, and the characteristics and factors of musical influences are explored by using software such as Gephi and SPSS. Through principal component analysis, three principal components were obtained, which were used to analyse the music metrics. And music metrics is studied by applying important correlation theories. The study of this project can help music lovers to further understand different types of music.
Keywords: music genre; popularity; principal component analysis; PCA; Pearson correlation coefficient; PCC; regression analysis; RA.
New Paradigms for the Sustenance of Live Theatre in Nigeria amidst the Pandemic: An Evaluation of First Ever Drive-in Theatre in Nigeria
by Agozie Ugwu, Uche-Chinemerem Nwaozuzu
Abstract: The outbreak of corona virus is heralded with the dawn of strange situations around the world. The world was in lockdown for months in 2020. The prohibition of social gathering affected live theatre and prompted measures that have been put in place by health experts to curtail the widespread of the Virus. The use of facemask, washing of hands and others are the protocols in place to stop the spread of the virus. The entertainment industry is one of the sectors that have been affected by this pandemic. Live theatre performance in Nigeria is one of the areas of the entertainment industry that has reinvented itself amidst the pandemic. The idea of drive-in theatre is an ongoing experiment in Nigeria that seems to be at the forefront of readapting live theatre. This paper evaluates Mosaic Theatre Productions (MTP) execution of first ever drive-in theatre in Nigeria.
Keywords: drive-in theatre; digital theatre; pandemic; new paradigm; Nigerian-theatre; Nigeria.
Study the executive tricks of cultural advertising with an emphasis on interactive art in the years2000-2020
by Mohsen Ali BabaeiShahraki, Abdul Khaliq Dastmardi, Somayeh Rasoulipour
Abstract: he concept of advertising means orienting oneself to public opinion; so today, mass media advertising, including urban advertising, which is one of the main sources of information, can promote the culture of a society. And these media play an important role in changing the level of societys culture. In fact, media advertising has led to many changes in the lifestyle, values and culture of the audience. Therefore, in this research, an attempt has been made to examine the executive tricks in cultural advertising and its features in order to convey the message effectively to the audience. To achieve this goal, a descriptive-analytical method has been used and its information has been collected in a library manner. Finally, using the obtained data, it has analysed samples of the worlds cultural and cultural urban advertisements. As the results of this study show, the method of interaction with executive techniques such as
Keywords: urban advertising; cultural advertising; interactive art; interactive media.
Selection of the Most Relevant Online English Semantic Art Translation in Cross-Lingual Information Retrieval based on Speech Signal Analysis Model
by Yuji Miao, Yanan Huang
Abstract: In the cross language information retrieval environment, semantic ontology model matching and feature extraction are needed for semantic translation processing and semantic information analysis. Hence, the efficient model should be designed. There are some semantic conflicts in cross semantic information retrieval database, which seriously affect the accuracy of language translation and information retrieval. Therefore, it is necessary to design the most relevant semantic translation in cross language information retrieval. Voice is the most common way of communication so far. In this paper, speech signal analysis and extraction technology is used to improve the accuracy of art cross language information retrieval. Experimental results show that the retrieval rate of the proposed method is higher than the traditional method. This study combines the art factor with the technology to reach the goal of the comprehensive analysis.
Keywords: Speech Signal Analysis; Signal Transmission; Linguistics; Information Retrieval; Relevance English Teaching; Semantic Art Translation.
Intelligent color matching method for 3D character animation based on texture features
by Fei Tang
Abstract: In order to overcome the problems of low matching degree and long matching time in traditional intelligent colour matching methods of 3D character animation, this paper proposes a colour intelligent matching method based on texture features. Three parameters H, S and V are taken as the main parameters of 3D character animation colour recognition, and the animation colour is compared with the colour quantisation template. According to the comparison results and colour difference formula, the animation colour recognition is realised. On this basis, SIFT algorithm is used to obtain colour features of 3D character animation, and clonal selection algorithm is used to realise colour intelligent matching of 3D character animation. The experimental results show that the accuracy rate of colour feature extraction is always above 96%, the colour matching degree is always above 97%, and the average colour matching time is 0.4 s. The practical application effect is good.
Keywords: texture features; 3D character animation; animation color; intelligent matching; clonal selection algorithm.
Color correction method of interior decoration engineering based on dense convolution neural network
by Chuan-qin Zhang, Hongtao Xing
Abstract: In order to solve the problem of long correction time existing in traditional methods, this paper proposes a colour correction method for interior decoration engineering based on dense convolutional neural network. For the colour deviation detection of interior decoration engineering, according to the detection results, the coordinated colour matching, colour matching harmony and visual comfort are taken as the colour correction objectives, and the calibration objective function is designed. The colour feature points matching and extreme point detection are carried out by using the objective function. According to the test results, the dense convolution neural network is used to correct the colour of interior decoration engineering and output the correction results. The experimental results show that the research method can improve the effect of colour correction, reduce the correction time, the mean error and the median error of colour deviation angle.
Keywords: Dense convolution neural network; Interior decoration engineering; Color correction; Color deviation.
Recognition method of dance rotation based on multi-feature fusion
by Yang Liu, Meiyan Fan, Wenfeng Xu
Abstract: There are some problems in traditional dance rotation recognition methods, such as low accuracy of contour superposition and low recognition rate. A dance rotation recognition method based on multi-feature fusion is proposed. The background noise subtraction method is used to separate the human motion regions in the foreground of the video data, and the contour features of each frame image of the preprocessed dance video are superimposed to obtain the direction gradient histogram features of the dance action information. According to the law of optical flow, the feature vectors of the histogram of optical flow direction are normalised. According to the shape and motion characteristics of human dance in dance video, the dance rotation recognition classifier is constructed to complete the dance rotation recognition based on multi-feature fusion. The experimental results show that the proposed method has higher accuracy of 97% and lower error rate of 0.7%.
Keywords: multi-feature fusion; mesh division; directional gradient; optical flow field;.
Criticizing Government Regulations On Music Royalty In Indonesia And Some Copyright Issues Of Music Works In The Digital Space
by Aris Setiawan
Abstract: This research aims to critically examine Government Regulation Number 56 of 2021 concerning music royalty management in Indonesia. The regulation aligned with the widespread piracy of musical works in Indonesia, thus placing copyright owners not getting a fair share of royalties. But the rule does not address the issue of royalties in the digital realm, such as YouTube. The digital realm is the root of the problem where the Indonesian music industry cannot develop well. This study uses a phenomenological approach and critical studies. Phenomenology as a research approach seeks to describe the phenomenons essence by exploring the perspectives of the existing problems. At the same time, the critical approach is used as an evaluation bridge. The results of this study are in the form of critical findings, which are expected to become recommendations for policymakers regarding the arrangement of music royalty regulations in Indonesia in the future.
Keywords: music; royalty; piracy; government regulation; digital space; phenomenology; critical studies; copyright; music artists; music industry.
Research on the Development and Experience of Popular Music Single with Interactive Lyrics and Composition
by Kuei Yang Chiu, Wen-Hung Chao
Abstract: The technological progress and internet penetration, Chinese pop music has copious innovation opportunities. This study developed a
Keywords: interaction; interactive music; interactive; popular music; interactive movie; innovation diffusion theory; consumer innovativeness; music video.
METAPHOR IN PLASTIC ARTS: EXAMPLE OF PORTRAIT SCULPTURE IN NIGERIAN ART SCHOOLS
by Francis Ebunola Allan Oladugbagbe
Abstract: The scope of sculpture is scholastically wide in theory and practice. In Nigeria, fine and applied arts or creative arts departments in tertiary institutions teach sculpture, the practice of which is executed in relief and in the round. They could be Marquette or life-sized. These circumstances are often determined by a combination of factors; namely, curriculum, art lecturer, student and, most importantly, space. A concise inventory of portrait sculptures is neither existing in any form nor given adequate scholarship attention in the past four-and-half decades in Nigerian higher art institutions. The dearth of literatures in this direction needs to be gradually reversed because of the deep socio-cultural significance of the sculpture. This paper, therefore, analyses the form, style, theme, and medium of plastic arts, and positions the images as a source of future academic outlet for portrait sculpture survey in Nigeria. It adopts both primary and secondary methods. Accordingly, direct field research method is employed for the sample examination. It is observed that placing of portrait sculptures on the garden floor in UNN tends to inspire inadvertent socio-cultural and political interpretations for which scholastic trajectory can place emphasis on institutionalised stylistic posture of image-on-the-ground symbolism of art.
Keywords: metaphor; plastic arts; portrait sculpture; Nigerian art schools.
Virtual Reality Art as an Innovative Buddhist Learning Tool
by Gomesh Karnchanapayap, Atithep Chaetnalao
Abstract: From paintings, sculptures, print, to digital media, art and technology have always been integral elements used to create Buddhist learning tools since ancient times. With the rise to mass acceptance of virtual reality, the new art form can innovatively be developed as an effective Buddhist learning tool. The VR artworks from this research are the results of merging technological advancements and art with the Buddhist faith to construct a ground-breaking Buddhist learning tool. The artworks enable multi-level learning experience for the audience. First, learning by sensory perceptions within VR makes the audience
Keywords: virtual reality; Buddhist learning tool; virtual reality art.
Environmental Art Social Networks Modelling and Information Mining Framework based on Green Computing
by Yan Tian
Abstract: The number of internet information is growing exponentially, with hundreds of millions of web pages that require a large demand on the computational efficiency. Users in social media can establish various relationships, which results in a variety of virtual online social networks. Social network service data is essentially a network data structure, and e-commerce website data can also be abstracted as a two-part graph composed of users and goods. In recent years, with collaborative filtering, local diffusion and other algorithms widely used in the recommendation system of e-commerce websites, network information mining has brought huge benefits for e-commerce websites, and the user experience has been improved rapidly. This paper studies the environmental art social network modelling and information mining model based on green computing. The novel computational model is designed for the systematic construction and algorithm is applied to real applications. The experimental results show effectiveness of the proposed method.
Keywords: green computing; cloud computing model; environmental art; social network; modelling; information mining.
Integrated eRosary?Design of a Rosary Application Focusing on Practical Use
by Takayuki Fujimoto
Abstract: In this paper, the authors aim to reproduce a software version of a rosary (eRosary) that is used for Christian worship. Various rosary applications have been released before. However, most of them are limited to assisting functions such as reciting prayers from the rosary and playing background music/displaying images to set the mood. It is difficult to suggest that these applications could entirely replace a standard rosary. A product that could substitute for an existing rosary has been released officially by the Roman Catholic Church, but there are still some challenging points: an extra device other than a smartphone is required, and the price is expensive. Therefore, in this paper, we propose and develop an application that can provide all of the necessary functions on the smartphone alone and replace the standard rosary in respect to practicability. The prototype application covers almost all the functions and needs required by rosary users. To the best of the authors knowledge, there is no such rosary application, and the novelty is extremely high.
Keywords: bible media informatics; eRosary; smartphone application; rosary; prayer application; devotion application.
Music emotion recognition method based on multi feature fusion
by Yali Zhang
Abstract: There are some problems in music emotion recognition, such as large root mean square error of recognition results and low Pearson correlation coefficient. The music signal is divided into frames by window function, and the noise in the music signal is reduced by the time domain endpoint detection, and the music signal is preprocessed. The characteristics of pitch change, gene rise and fall, speech speed and gene slope were extracted by Mehr frequency cepstrum coefficient. According to the extracted music emotion features, the multi-feature fusion kernel function is constructed. Based on the fusion results, the multi-level SVM emotion recognition model is built with the support vector mechanism to realise music emotion recognition. Experimental results show that the root mean square error of the proposed method is always within the range of 0.02, and the highest Pearson correlation coefficient is about 0.9.
Keywords: music signal; feature extraction; feature fusion; emotion recognition; support vector machine.
Edge denoising of art illustration image based on contour feature recognition
by Wei Zhao
Abstract: In order to solve the problems of low precision and long time-consuming in traditional edge denoising methods of art illustration image, an edge denoising method of art illustration image based on contour feature recognition is proposed. The edge of art illustration image is segmented, and the feature target value and background value are extracted. By calculating the same degree of edge data in each kind of features, the edge feature classification of art illustration image is realised with the help of naive Bayes classification matrix. The edge noise region of the image is determined, and the wavelet descriptor in the contour descriptor is used to smooth the edge noise region of the art illustration image to complete the edge denoising of the art illustration image. Experimental results show that the edge denoising accuracy of the proposed method is about 95%, and the denoising time is only 2.1 s.
Keywords: contour features; art illustration images; edge denoising; feature extraction.
Research on the Extraction Method of Painting Style Features Based on Convolutional Neural Network
by Hua Jiang, Ting Yang
Abstract: In order to overcome the problem of low accuracy in the traditional method for style feature extraction of painting works, this paper proposes a method for style feature extraction of painting works based on convolution neural network. Firstly, the parameters in the digital image of painting works are quantised, and then the feature parameters are fused by fusion technology and used as input information. Then the wind fusion features of painting works are extracted by using the deep hash coding of triple recombination structure in convolutional neural network. The experimental results show that the Precision value of this method always stays at a high level with the change of the Recall value, which can be kept above 0.7, and the AP value is always above 0.9. It shows that this method has strong adaptability and high precision of feature extraction.
Keywords: paintings; style features; convolution neural network; CNN; deep hash coding; feature extraction.
Research on color correction algorithm of art works based on mapping rules
by Ta-hong Zhang, Ting Yang
Abstract: In order to overcome the problems of large correction error and low correction efficiency existing in the traditional colour correction algorithm of art works, this paper proposes a colour correction algorithm of art works based on mapping rules. The algorithm establishes a colour deviation detection model based on the colour degree and naturalness of the image, and detects the colour deviation of the image of art works. Using the mapping rules to calculate the colour deviation of the colour deviation image, based on the colour deviation calculation results, the improved gray world method based on standard deviation weighting is used to correct the colour of art works, and the colour correction of art works is completed. Experimental results show that the proposed algorithm has good image colour and naturalness, small angle error, high correction efficiency, and the maximum correction error is less than 0.2.
Keywords: mapping rule; image detection; colour deviation; gray world method; colour correction.
Application of Fourth Industrial Revolution Technologies in Contemporary South African Art
by Siyanda Xaba, Xing Fang, Dhaneshwar Shah, Kaiwen Yang
Abstract: Significant studies have looked into Fourth Industrial Revolution (4IR) technology, particularly in the science and technology industry. These technologies range from AI, robotics, 3D printing technology, IoT, CPS, and digital technologies. Unfortunately, there is a dearth of research regarding the operation of 4IR technologies in the arts. The 4IR is digital, and creativity, as well as critical thinking, are at the centre of this revolution. Creativity and critical thinking are at the centre of art practice. Interestingly, although there is an attempt by scholars to link creativity and critical thinking in 4IR, little information is available on research regarding the application of 4IR technologies in the arts. This study aims to bridge the gap that exists in literature by discussing 4IR in the context of visual art. Furthermore, the paper attempts to look into digital art technologies as part of the 4IR.
Keywords: 4IR technology; digital art technologies; contemporary art; visual art; South Africa.
Product Form Innovation: A Morphodynamic Factors-Driven Approach
by ZhiPeng Zhang, Jianning Su, Xiong Li, WenJin Yang
Abstract: In this paper, a morphological dynamics factors-driven product form concept design method is proposed. The approach is based on three modules: analysis and capture of the set of product morphological dynamics factors, morphological algorithm design and computation, and morphological optimisation. The proposed approach has two advantages: linking the dynamic factors to uncertainty perception and using parametric modellers to improve the adaptability of the modelling schemes through the continuous interaction of knowledge between designers, users, and engineers and the configuration of external parameters in terms of representational behaviours The modeller is constructed with adaptive and fast response features to quickly obtain 3D product form solutions by inputting different 2D sketch features to the program. This study demonstrated the effectiveness of the method through a case study of helmet morphology design.
Keywords: morphodynamic; factors-driven; product morphology; conceptual design; computational design.
by Nitin Paharia, Rajesh Gupta, R.S. Jadon, Sanjay Kumar Gupta
Abstract: Recognising human activity in video is a highly challenging and complex task because video contains lots of information along with complex variations. Yoga-asana recognition is one of the instances of human activity recognition that gained attention in last decade across the globe. In this paper, we developed an appearance based recognition system for yoga-asana in video. The system has been implemented using end-to-end deep learning pipeline that includes convolutional neural network (CNN) and bidirectional long short-term memory (LSTM) network. Firstly, each video is down-sampled to 20 frames. Thereafter, spatial features are extracted from each frame and then in turn passed on to bidirectional LSTM for learning sequential information. Finally, Softmax classifier is applied on spatio-temporal representation of video for assigning one of the seven yoga-asana labels to it. For this study, we also created a customised dataset of seven yoga-asana (Bhujangasana, CatCow, Trikonasana, Vrikshasana, Padmasana, Shavasana, and Tadasana). The system achieved average test accuracy of 96.67% on customised dataset in 20-fold cross validation which is comparative to related work.
Keywords: computer vision; convolutional neural network; CNN; long short-term memory; LSTM; human activity recognition; HAR; yoga-asana.