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检索条件"机构=Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture"

共 127 条记录，以下是91-100 订阅

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Research on Color Harmony Evaluation Method based on Color Complexity Measure

Research on Color Harmony Evaluation Method based on Color C...

引用

culture-oriented Science & technology (ICCST), International Conference on

作者： Yanting Gao Jingjing Zhang Shuang Wang Yuncong Peng Aixia Tang School of Information and Communication Engineering Communication University of China Beijing China Ministry of Culture and Tourism Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China) Beijing Key Laboratory of Modern Entertainment Technology (Communication University of China) School of Computer Science and Cybersecurity Communication University of China Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

Color harmony is an important factor affecting the aesthetic feeling of images and plays an important role in visual perception. It can evaluate the feasibility of images by constructing the computational model of human aesthetic thinking. In this paper, a color harmony evaluation method based on color complexity was implemented. Given the classical color harmony model which is suitable for the simple color combination but not suitable for the complex image, and the local feature redundancy caused by grid sampling, an adaptive sampling based on CCM(color complexity measure) was implemented. Then, K-means was adopted to extract local color harmony features. Finally, a model was constructed between local color harmony features and the overall color harmony by SVM. The results show that the method implemented in this paper can represent the color harmony of complex images accurately and effectively.

关键词： Image color analysis Support vector machines Feature extraction visual perception Wheels Computational modeling Complexity theory

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A Method of Improved Automatic Light Tracing

A Method of Improved Automatic Light Tracing

引用

International Conference on Dependable systems and Their Applications (DSA)

作者： Yujian Jiang Yanqiu Ren Kai Song Wei Jiang Key Laboratory of Acoustic Visual Technology andlntelligent Control System Ministry of Culture and Tourism (Communication University of China) Beijing China Beijing Key Laboratory of Modem Entertainment Technology (Communication University of China) Beijing China School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (数字)9781728160573

ISBN: (纸本)9781728160580

At present Auto-Tracking technology attracted increasing attention in the field of stage lighting. Most of the existing automatic lighting tracing methods adopt indoor positioning technology to acquire the location parameters of the tracing object. Then the location parameters were converted into the control data of moving light for automatic tracing. The main problems are as follows: one is the positional errors of special light position such as front light and fixed-point light. The other is the miss tracking of moving targets. In this paper, according to the projection requirements of front light and fixed-point light, the existing tracing model is improved. The error between the spot and the actual position is analyzed. Test results show that the accuracy of the upper left and upper right directions is relatively high. The bigger the curvature amplitude is, the bigger the error is. At the same time, the test data provide theory evidence for the setting of the tracing light position and the design of the performance route.

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Emotion classification of film and television scene images for audiences

Emotion classification of film and television scene images f...

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2019 International Joint Conference on Information, Media, and Engineering, IJCIME 2019

作者： Su, Zhibin Qian, Yahong Ren, Hui Lv, Chaohui Zhang, Xiaoyi Li, Weiwei Key Laboratory of Acoustic Visual Technology and Intelligent Controla System Communication University of China Ministry of Culture and Tourism School of Information and Communication Engineering Communication University of China Beijing China CITVC KEHUA CO. LTD. Technology Service Branch Beijing China

ISBN: (纸本)9781728155869

The purpose of the research on emotion classification of film and television (TV) scene images is to hope that the computer can simulate the audience's emotional perception to judge positive or negative emotional trends of the image. In this paper, from the perspective of emotional semantics, a method of the emotion classification about the film and TV scene image is proposed. Firstly, the film and TV scene image dataset were established and assessed based on the subjective evaluation experiment. Then the theory of psychology and photographic art was used to extract image emotional features. Finally, particle swarm optimization (PSO)-support vector machine (SVM) algorithm based on feature importance dimension reduction was used for building the classifier. The experimental results show that the image dataset initially established in this paper can be helpful to the subsequent study on emotion classification of the film and TV scene image, and the accuracy of the positive and negative emotion classifier on this dataset is 0.87, which conforms to audience's emotional perception of the film and TV scene image. © 2019 IEEE.

关键词： Support vector machines

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A Study of Color-emotion Image Set Construction and Feature Analysis

A Study of Color-emotion Image Set Construction and Feature ...

引用

International Conference on Computer and Information Science (ACIS)

作者： Wei Jiang Shuang Wang Yanan Su Jingyu Liu Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China)

This paper mainly studies the method of feature extraction of image set, and makes an in-depth analysis between objective features and subjective features. Firstly, a color-emotion image set was constructed with the presentation of an image set construction scheme facing to the research of audiovisual fusion information processing. Secondly, this paper improved the color dominate extraction algorithm and the membership function of cool-warm attribute to acquire the better corresponding to human visual perception. Thirdly, a subjective evaluation experiment was introduced to extract subjective features. Finally, on the basic of feature extraction, this paper makes an in-depth analysis with these features, which has some interesting findings.

关键词： Color Feature extraction Image color analysis Standards visualization Clustering algorithms Reliability

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The Association Between Timbre of Musical Sound and Texture

The Association Between Timbre of Musical Sound and Texture

引用

International Conference on Computer and Information Science (ACIS)

作者： Wei Jiang Xiaoyi Zhang Jingyu Liu Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China)

This paper mainly studies the association between the timbre of music and the texture of images, and constructs the mathematical model of the association. Firstly, extract texture features, and system clustering and multidimensional scaling are carried out on the images in Brodatz texture database to select 18 texture images to be used for subjective evaluation experiment. Through the subjective evaluation experiment, the data of the timbre perceptual features and the matching relationship between timbre and texture are obtained. Based on this data, the Pearson correlation coefficient about matching (or mismatching) timbre-texture feature pairs is calculated respectively, the absolute value of the correlation coefficient peaked at 0.752, which verifies the strong association between them. Logistic, random forest and BP neural network are used to predict the matching relationship between texture and timbre, and prediction models with high accuracy were obtained. The precision of BP neural network reached 70%, which can better predict the matching relationship between texture and timbre.

关键词： Timbre Feature extraction Instruments Correlation coefficient Correlation Image color analysis

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Analysis and Modeling of Timbre Perception Features of Chinese Musical Instruments

Analysis and Modeling of Timbre Perception Features of Chine...

引用

International Conference on Computer and Information Science (ACIS)

作者： Wei Jiang Jingyu Liu Zijin Li Jiaxing Zhu Xiaoyi Zhang Shuang Wang Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China) Ministry of Culture and Tourism Musicology Department China Conservatory of Music Beijing China

This paper studies the analysis and modeling of timbre perception features of musical sound. Firstly, a timbre material library containing 74 samples was constructed, and an objective acoustic parameter set containing 76 parameters was constructed. Then, for each timbre evaluation term, method of successive categories is used for subjective evaluation experiment, and the experimental data of timbre perception features are obtained. Finally, the mathematical model of timbre perception is established by support vector regression. The experimental results show that the model has good prediction ability for four timbre perception features.

关键词： Timbre Predictive models Harmonic analysis Analytical models Support vector machines

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Joint Depth Estimation and Semantic Segmentation with Adversarial Multi-task Network

Joint Depth Estimation and Semantic Segmentation with Advers...

引用

culture-oriented Science & technology (ICCST), International Conference on

作者： Hui Ren Nan Gao Jia Li State Key Laboratory of Media Convergence of Communication Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of China Beijing China School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

Some exiting works have explored the promotion between depth estimation and semantic segmentation. These works are usually based on convolutional neural networks, which extract compact features and map the relationship between input and output according to specific tasks. In this paper, we introduce a novel adversarial training strategy, that is, generator produces the semantic segmentation map and depth map, and then the discriminator can judge the authenticity of the synthesized color image, thereby supervising the output of the network during back propagation. We use the adversarial loss combined with the reconstruction loss function to supervise the model, and find that the adversarial loss function which is seen as a global supervision can further optimize the output. We use 200 color images from Kitti dataset with semantic segmentation ground truth as the training set, and train the network in an end-to-end manner. The experimental results show that the adversarial training method is well applied to the multi-task training combining semantic segmentation and depth estimation, and can further improve the quantitative performance of depth estimation.

关键词： Semantics Estimation Generative adversarial networks Generators Training Task analysis Mathematical model

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Stage Actor Positioning Method Based on RealSense Point Cloud

Stage Actor Positioning Method Based on RealSense Point Clou...

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Information, Media and Engineering (IJCIM), International Joint Conference on

作者： Chaohui Lv Lexuan Yang Min Li Jun Yin School of Information and Communication Engineering Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (数字)9781728155869

ISBN: (纸本)9781728155876

A novel and convenient method for human positioning based on computer vision is proposed. The new camera Realsense D435 from Intel is used to provide richer and more effective visual information. The positioning problem can be simplified to the conversion problem between point cloud and space coordinate system. Experimental results indicated that only several test points were needed to establish the conversion relationship between the two coordinate systems, thereby obtaining the position of the person. The accuracy meets the demand of the stage performance.

关键词： Three-dimensional displays Cameras Mathematical model visualization Calibration Real-time systems

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Monocular Depth Estimation with Traditional Stereo Matching Information

Monocular Depth Estimation with Traditional Stereo Matching ...

引用

International Conference on systems and Informatics (ICSAI)

作者： Hui Ren Nan Gao Jia Li Ministry of Culture and Tourism Beijing Key Laboratory of Modern Entertainment Technology School of Information and Telecommunication Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Beijing China

ISBN: (数字)9781728152561

ISBN: (纸本)9781728152578

Monocular depth estimation is to perform pixel-level depth estimation on single perspective image, and the methods based on deep learning have shown superior effect for the challenging task. However, the supervised depth estimation methods need costly ground truth labels, which require professional equipment. To solve this problem, we study the unsupervised monocular depth estimation algorithm combining traditional stereo knowledge. We use the unsupervised network based on the reconstruction method as the baseline, which can be trained without direct supervision from ground truth depths leveraging image synthesis on sequences or multi-views images, so that it can improve the accuracy of prediction results without applying any annotations such as LIDAR depth in KITTI. Experiments results on the publicly database KITTI (Eigen split) have shown the promising effectiveness of the proposed method, and compared with state of the art unsupervised algorithms, it has achieved competitive performance in objective evaluation indicators.

关键词： Estimation Image reconstruction Training Task analysis Prediction algorithms Databases visualization

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Vehicle Object Detection Based on RGB-Camera and Radar Sensor Fusion

Vehicle Object Detection Based on RGB-Camera and Radar Senso...

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Information, Media and Engineering (IJCIM), International Joint Conference on

作者： ZhongTong Li Ming Yan Wei Jiang Pin Xu School of Information and Communication Engineering Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (数字)9781728155869

ISBN: (纸本)9781728155876

Object detection has always played a major role in the field of computer vision. With the development of faster region-based convolutional neural network (faster-RCNN), single shot multi-box detector (SSD), You Only Look Once (Yolo) and other deep learning networks, 2D object detection has been developed well developed. However, in some key areas, such as driverless vehicles and artificial intelligence robots, cannot meet the requirements of tasks just by detecting two dimensional (2D) objects. So we need to get the three dimensional (3D) position of the object. In 3D object detection, it is difficult to obtain object position information only by red-green-blue (RGB) image. There are some methods to get the 3D position of the target through the point cloud data set. Therefore, this paper proposes a deep learning network, which can combine both color image information and point cloud geometry information, while using MobileNet V3 as the backbone network greatly enhances the operation speed. The region proposal networks (RPN) layer in faster-RCNN is migrated to the network. After testing, the method proposed by us improves obviously in speed and recognition accuracy compared with the previous methods.

关键词： Three-dimensional displays Two dimensional displays Feature extraction Cameras Radar Convolution Object detection

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