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检索条件"任意字段=Conference on Visual Communications and Image Processing"

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Data processing Technology of UAV Tilt Photogrammetry Based on Multi-source Geographic Information

Data Processing Technology of UAV Tilt Photogrammetry Based ...

引用

Power, Electrical Engineering, Electronics and Control (PEEEC), International conference on

作者： Fan Yang Cong Jing College of Road and Bridge Engineering Jilin Communications Polytechnic Changchun China Career Center Jilin Polytechnic of Water Resources and Electric Engineering Changchun China

ISBN: (数字)9798350378917

ISBN: (纸本)9798350378924

With the rapid development of UAV technology, UAV tilt photogrammetry has become one of the important means to obtain geographic information data. However, due to the challenges of diverse geographic information data sources and inconsistent data quality, how to effectively integrate multi-source geographic information data has become a key issue. Aiming at this problem, this study proposes an image fusion method based on deep learning, aiming at improving the fusion quality and processing efficiency of geographic information data. Firstly, the basic principle and data acquisition process of UAV tilt photogrammetry are introduced, including aircraft selection, route planning, selection of photographic equipment and sensors. Then, the methods and technologies of multi-source geographic information fusion are discussed, including data preprocessing, feature extraction, data registration and image fusion. Then, the specific implementation steps and algorithms of the image fusion method based on deep learning adopted in this paper are expounded. Through the verification on experimental data sets, the advantages of the proposed method are demonstrated, including fusion effect, model performance and processing efficiency. Finally, the research results are summarized and analyzed, and the significance and application prospect of this method in the fusion of multi-source geographic information are pointed out.

关键词： Deep learning Training Accuracy Soft sensors Process control Autonomous aerial vehicles visual effects Reliability image fusion Photogrammetry

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Temporal Scalable Coding For Dynamic Meshes

Temporal Scalable Coding For Dynamic Meshes

引用

IEEE International conference on image processing

作者： Jianfeng Xu Haruhisa Kato Kei Kawamura Advanced Visual Communication Laboratory KDDI Research Inc 2-1-15 Ohara Fujimino-shi Saitama Japan

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

This paper presents the first implementation of temporal scalability in the ongoing standard for Video-based Dynamic Mesh Coding (V-DMC), a crucial enhancement that enables bitstream adaptation to diverse network conditions and device capabilities. While displacement and texture, two of the V-DMC’s sub-bitstreams, already benefit from existing video codec temporal scalability, the non-video basemesh sub-bitstream lacks this feature. To address this gap, we propose an adaptive coding structure designed for the basemesh. Moreover, we propose a novel cost function to adaptively select the frame type between intra-frame and inter-frame in this coding structure. Our experimental results demonstrate significant improvements in coding efficiency compared to the original V-DMC, i.e., the total BD-rates of D1, D2, Luma, Cb, and Cr averaged across all eight test sequences are -15.1%, -15.0%, 0.3%,-9.9%, and -8.4 %, respectively.

关键词： image coding Scalability Estimation Cost function Video codecs Standards Adaptive coding

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LSB-Based visual image Encryption Scheme in Cloud Environment

LSB-Based Visual Image Encryption Scheme in Cloud Environmen...

引用

IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Sifei Zheng Xiaolong Liu Riqing Chen Shyan-Ming Yuan Chia-Chen Lin College of Computer and Information Sciences Digital Fujian Institute of Big Data for Agriculture and Forestry Fujian Agriculture and Forestry University Fuzhou China Department of Computer Science National Chiao Tung University Hsinchu Taiwan Department of Computer Science and Information Management Providence University Taichung Taiwan

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Preventing multimedia data in cloud environment from leakage is a significant and imperative issue in the modern information-oriented society. Many encryption schemes have been proposed to convert original images into noise-like images. However, the noise-like images are conspicuous visual signs to attract the attention of attackers, and thus lead to large quantities of attacks. In order to solve the problem, this paper propose a visual encryption scheme to convert an original image into another visually meaningful image to elude the attacker's attention and ensure the security of the image. image data security is implemented by pre-encryption procedure and the meaningful appearance of encrypted image is based on Least significant bit (LSB) substitution, respectively. The experimental results demonstrate the superiority of the proposed scheme in terms of excellent encryption performance. The proposed scheme can protect original images that require a higher level of security compared with existing encryption schemes.

关键词： Encryption Cloud computing visualization Transforms Agriculture

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Surveillance from above: A detection-and-prediction based multiple target tracking method on aerial videos

Surveillance from above: A detection-and-prediction based mu...

引用

Integrated communications, Navigation and Surveillance conference, ICNS

作者： Xiaolong Jiang Xianbin Cao School of Electronic and Information Engineering Beihang University Beijing China

ISBN: (纸本)9781509021505

Along with the rapid development of the Unmanned Aerial Vehicle (UAV) technology, visual traffic surveillance is now granted with a great opportunity to become mobilized. Airborne mounted surveillance cameras are suitable to work as an ideal alternative to the traditional stationary cameras to provide more coverage with lower expense. For realizing such a solution, in this paper we engineered an efficient multiple targets tracking method designed for aerial videos captured by low-altitude UAVs. This method combines the strengths of both Tracking-by-Detection (T-by-D) and Tracking-by-Prediction (T-by-P) framework, where the target detection is first performed with an integrated motion detection module, then the traditional data association component is substituted by a detection-and-prediction based category-free blob tracking scheme. To overcome the camera jitter introduced by the UAV platform, a reliable image registration method is also implemented as a pre-processing operation. Extensive experiments have demonstrated the effectiveness and reliability of the proposed method.

关键词： Target tracking Surveillance Videos Cameras image registration Feature extraction

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Precise weld line detection on a large-scale structure

Precise weld line detection on a large-scale structure

引用

International conference on Industrial Electronics, Control and Instrumentation

作者： A. Ishii H. Yoshida K. Suzuki Y. Ochi Department of Mechanical and Control Engineering University of Electro-Communications Chofu Tokyo Japan

In the automation of arc welding with visual sensors, it is necessary to precisely detect the weld line. However, for large scale structures such as a steel tube transmission tower shown in the present study, it is not easy to maintain reliability of the weld line detection. The proposed method utilizes two important features in the welding of large-scale structure. They are based on the use of CAD/CAM data and the torch control. The proposed method is applied to detect straight and arc weld lines in some practical images. The results are satisfactory and successful in precisely detecting weld lines and weld tacks.

关键词： Welding Large-scale systems image edge detection Automation Steel Pixel Poles and towers image processing Automatic testing Turning

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Rapid Mobile Object Recognition Using Fisher Vector

Rapid Mobile Object Recognition Using Fisher Vector

引用

Asian conference on Pattern Recognition (ACPR)

作者： Yoshiyuki Kawano Keiji Yanai The University of Electro-Communications Tokyo Tokyo Japan

We propose a real-time object recognition method for a smart phone, which consists of light-weight local features, Fisher Vector and linear SVM. As light local descriptors, we adopt a HOG Patch descriptor and a Color Patch descriptor, and sample them from an image densely. Then we encode them with Fisher Vector representation, which can save the number of visual words greatly. As a classifier, we use a liner SVM the computational cost of which is very low. In the experiments, we have achieved the 79.2% classification rate for the top 5 category candidates for a 100-category food dataset. It outperformed the results using a conventional bag-of-features representation with a chi-square-RBF-kernel-based SVM. Moreover, the processing time of food recognition takes only 0.065 seconds, which is four times as faster as the existing work.

关键词： Vectors image color analysis image recognition Support vector machines Feature extraction Histograms Mobile communication

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A Method Using Texture and Color Feature for Content-Based image Retrieval

A Method Using Texture and Color Feature for Content-Based I...

引用

2015 IEEE International conference on Computer and communications(ICCC 2015)

作者： He Zhang Xiuhua Jiang Information Engineering School Communication University of China

With the rapid growth of image database, contentbased image retrieval(CBIR) technology with its high value in theory and application has become a hot topic in the field of image processing. A retrieval method which combines color and texture feature is proposed in this paper. According to the characteristic of the image texture, we can represent the information of texture by fusion algorithm combines Gabor transform and edge histogram. The color histogram in HSV color space is chosen as the color feature, and the blocking and fuzzy color histogram is proposed in this paper. The experiment results show that this method is more efficient than the traditional CBIR method based on the single visual feature and method combining color and texture like CEDD.

关键词： image retrieval Texture feature Color feature Fusion

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Explicit-NeRF-QA: A Quality Assessment Database for Explicit NeRF Model Compression

Explicit-NeRF-QA: A Quality Assessment Database for Explicit...

引用

IEEE visual communications and image processing (VCIP)

作者： Yuke Xing Qi Yang Kaifa Yang Yiling Xu Zhu Li Cooperative MediaNet Innovation Center Shanghai Jiao Tong University Shanghai China Department of Computer Science and Electrical Engineering University of Missouri-Kansas City USA

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

In recent years, Neural Radiance Fields (NeRF) have demonstrated significant advantages in representing and synthesizing 3D scenes. Explicit NeRF models facilitate the practical NeRF applications with faster rendering speed, and also attract considerable attention in NeRF compression due to its huge storage cost. To address the challenge of the NeRF compression study, in this paper, we construct a new dataset, called Explicit-NeRF-QA. We use 22 3D objects with diverse geometries, textures, and material complexities to train four typical explicit NeRF models across five parameter levels. Lossy compression is introduced during the model generation, pivoting the selection of key parameters such as hash table size for InstantNGP and voxel grid resolution for Plenoxels. By rendering NeRF samples to processed video sequences (PVS), a large scale subjective experiment with lab environment is conducted to collect subjective scores from 21 viewers. The diversity of content, accuracy of mean opinion scores (MOS), and characteristics of NeRF distortion are comprehensively presented, establishing the heterogeneity of the proposed dataset. The state-of-the-art objective metrics are tested in the new dataset. Best Pearson correlation, which is around 0.85, is collected from the full-reference objective metric. All tested no-reference metrics report very poor results with 0.4 to 0.6 correlations, demonstrating the need for further development of more robust no-reference metrics. The dataset, including NeRF samples, source 3D objects, multiview images for NeRF generation, PVSs, MOS, is made publicly available at the following location: https://***/YukeXing/Explicit-NeRF-QA.

关键词： Measurement Three-dimensional displays Correlation Accuracy image coding visual communication Video sequences Neural radiance field Distortion Rendering (computer graphics)

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Segmentation of visual images under complex outdoor conditions

Segmentation of visual images under complex outdoor conditio...

引用

International conference on communications and Signal processing

作者： T. Sathish kumar S. Pavya K. S. Rangasamy College of technology Namakal

Motion detection and segmentation of traffic vehicles in an outdoor environment, particularly under non ideal weather conditions, in the presence of camera noise and with variable or unfavorable luminance conditions is still an area of active research. Gaussian based background modeling is commonly used to detect moving objects in computer vision systems. However, it has some limitations it cannot effectively deal with sudden change in illumination, snowfall, fog, and repetitive motions such as swaying leaves. These nonideal outdoor conditions result in false motion detection. An alternative technique propose to detect and segment the moving vehicles by making use of dynamically adaptive threshold using the full-search sum of absolute difference (FSSAD) algorithm. Motion energy is obtained using sequence of frames that can be effectively be used to differentiate between moving vehicles and a dynamic background. Adaptive-motion threshold is used. It not only reduces the false motion but improves the computational efficiency as well.

关键词： Vehicles Meteorology Computational efficiency Algorithm design and analysis Filtering Manganese image resolution

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Cheque Information processing and Validation using Deep Learning

Cheque Information Processing and Validation using Deep Lear...

引用

communications and Information Technologies (GCCIT), Global conference on

作者： Suganthi K Darshan N Shenoy School of Electronics Engineering Vellore Institute of Technology Chennai

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388923

Understanding document images, such as invoices, is a difficult task. It necessitates reading the text as well as comprehending the document’s general structure. Conventional techniques first extract text using Optical Character Recognition (OCR), yet this method has drawbacks. In addition to being computationally costly, OCR can have trouble converting between various languages and document formats and introduce errors that can compound throughout the analysis *** is an OCR-free VDU (visual Document Understanding) model that challenges this paradigm. It does not even bother with the text extraction stage; it analyzes the document image straight. This creative strategy produces notable advancements. Donut performs at the cutting edge, which means it is quick and precise. This is a significant development in the realm of visual document understanding since it enables Donut to handle a greater variety of languages and document types. The model has been tested using BLEU scores and ROUGE scores over 3 parameters namely – payee name, amount in words and amount in figure. The model has also been tested over variety of sample sizes ranging from 50 to 1000.

关键词： Training Productivity visualization Target recognition Optical character recognition Transforms Streaming media Multilingual Data mining Testing

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