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检索条件"任意字段=3rd International Conference on Computer Vision and Pattern Analysis, ICCPA 2023"

共 459 条记录，以下是41-50 订阅

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A Binocular Stereo vision Packaging Dimension Measurement Algorithm Based on Improved SURF 3

A Binocular Stereo Vision Packaging Dimension Measurement Al...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Zhou, Xin Zhang, Zhigang School of Communication Engineering Chongqing College of Electronic Engineering Chongqing401331 China College of Information Technology Jiaozuo University Jiaozuo454003 China

ISBN: (纸本)9781510667563

To achieve non-contact automatic measurement of packaging cases in the transportation process of the logistics industry, such as secondary packaging, transshipment, and warehousing, a machine vision dimension measurement system based on binocular stereo vision was proposed. Firstly, the method of combining the SURF algorithm with FREAK descriptor improves the execution efficiency of the algorithm while ensuring the acquisition of better identification feature points;Then, the MISMATCHING feature points are eliminated through the PROSAC mechanism, and the initial disparity map is optimized using bilateral filtering. The spatial information of the measured object is obtained through three-dimensional reconstruction;Finally, a combination of Canny edge detection and Harris corner detection is used to extract the edge information of the object, and the geometric description of the external contour of the target object is obtained through line fitting and calculate the precise size of the measured object through the modified three-dimensional space volume. The experimental results show that this method can effectively identify and describe the shape of various specifications of the measured object, and the measurement error and real-time performance can solve the industrial requirements of the logistics industry. © 2023 SPIE.

关键词： Stereo image processing

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Dense Pedestrian Detection Based on Multiple Link Feature Pyramid Networks 3

Dense Pedestrian Detection Based on Multiple Link Feature Py...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Huang, Tao Yang, Siyu Yu, Tingjian Fu, Xiang Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China School of Software Nanchang Hangkong University Nanchang China

ISBN: (纸本)9781510667563

Pedestrian detection is widely employed in a variety of industries, including security, autonomous driving, and pedestrian flow statistics. However, because most pedestrians in real-world scenes are densely distributed with occlusion issues, scale variation and pose variability, majority pedestrian detection algorithms have low detection accuracy and a high miss detection rate. In this paper, we propose a new FPN neck module, Multiple Link Feature Pyramid Networks (MLFPN) for dense pedestrian detection, which innovative information transfer pathways and incorporation of Poly-Scale Convolution (PSconv) capable of long-range interaction into feature extraction tasks to reduce feature information loss and enhanced representation of effective pedestrian features, achieving 0.6MR-2, 0.35AP, and 0.21JI improvements on CrowdHuman dataset, improving detection accuracy and reducing missed detection rates. © 2023 SPIE.

关键词： Feature extraction

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Design and Exploration of a Virtual Reality-based Human-computer Interaction System 3

Design and Exploration of a Virtual Reality-based Human-comp...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Liu, Jie Jahng, SurngGahb University of Shanxi The graduate school of Advanced Imaging Science Chung-Ang University Korea Republic of The graduate school of Advanced Imaging Science Chung-Ang University Korea Republic of

ISBN: (纸本)9781510667563

First, data gloves were made. The STM32 microcontroller was selected for the data glove to collect hand motion pose data from the MPU6050 sensor, and the data was transferred to the Unity3D engine via a wireless Bluetooth module. The experiments show that the data glove can provide data to the system stably and the system does not lag. The HMM-based dynamic gesture recognition method is proposed. The hidden Markov model is studied in depth, and the gesture interaction recognition model is established by adding noise and normalization to the data generated by the data glove. The proposed algorithm has a correct recognition rate of more than 90% for all the eight defined gestures. Finally, This paper is based on virtual reality even though the research and integration of human-computer interaction systems has made some progress and breakthroughs in the new field of virtual reality. © 2023 SPIE.

关键词： Virtual reality

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Pedestrian multi-object tracking based on YOLOv7 and BoT-SORT 3

Pedestrian multi-object tracking based on YOLOv7 and BoT-SOR...

引用

3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Li, Tingting Li, Zhanbo Mu, Yuhong Su, Jie School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou China School of Cyber Science and Engineering Zhengzhou University Zhengzhou China

ISBN: (纸本)9781510667563

As a crucial component in the realm of computer vision, multi-object tracking has garnered widespread application in areas such as autonomous driving, smart transportation, and surveillance *** on YOLOv7 and BoT-SORT algorithms, this paper followed TBD (track by detection) framework. First, YOLOv7 served as the detector tasked with identifying the target and specifying its location within the frame. Then, the BoT-SORT algorithm was used to track the target based on the target detection results. The results are then tested on the MOT20 dataset. The experimental data show that on MOT20 data set, the accuracy of multi-object tracking reaches 69.36%, and the accuracy of multi-object tracking reaches 79.11%, which effectively solves the problems of target occlusion and frequent identity switching. The experiment proves that it still has good tracking effect under dim lighting and crowded complex scenes. It can achieve better tracking for the non-rigid target of pedestrians, and has higher accuracy than YOLOv7-DeepSORT and YOLOv7-ByteTrack. © 2023 SPIE.

关键词： Target tracking

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Machine vision-based measurement of air compressor crankshaft journal dimensions 3

Machine vision-based measurement of air compressor crankshaf...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Xi, Chenxin Ruan, Jingkui Liu, Anran Hubei University of Automotive Technology China

ISBN: (纸本)9781510667563

For the problems of slow speed, low efficiency, and labor intensity of manual measurement of crankshaft structure size of air compressor, a machine vision-based method for measuring crankshaft size of air compressor was proposed. Firstly, a bilateral retention filter was used to filter the grayscale image to ensure the crankshaft edge while smoothing the image. Then the smoothed image was binarized by an automatic threshold segmentation algorithm to segment the crankshaft and the background region. Finally, the sub-pixel edge contours of the image were extracted using canny as the localization function, and the edge contours of the crankshaft were obtained after segmentation, screening, and combination. Based on the extracted contour lines, the edge line regions were drawn, and the pixel distance between the two linear regions was calculated to obtain the diameter size of the crankshaft. The experimental results show that the accuracy of the diameter dimension calculated by this algorithm can reach 99.898% compared with the measured dimension, and the error was less than 0.03mm. © 2023 SPIE.

关键词： Crankshafts

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Object detection algorithm based on mixed dilated convolution pyramid 3

Object detection algorithm based on mixed dilated convolutio...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Yu, Tingjian Yuan, Zemin Huang, Tao Fu, Xiang Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China School of Software Nanchang Hangkong University Nanchang China

ISBN: (纸本)9781510667563

To address the problem that FPN in the one-stage object detection algorithm loses a large amount of semantic information after upsampling and downsampling fusion, leading to difficulties in detecting small objects in dense scenes. This paper proposes a new FPN structure, Residual dilated FPN(rdFPN), compared to the traditional FPN, which uses multiple Dilated Block instead of the standard convolution in the FPN horizontal structure to mix the receptive fields of different layers in the feature map and expand the object size range of the feature map, while improving the network's ability to extract features at different scales. Experimental results show that rdFPN improves the mAP of the one-stage object detection algorithms RetinaNet, FCOS, and GFL by 0.9%, 0.7%, and 0.8% on the MS COCO dataset, enough to improve the overall performance of the detector. © 2023 SPIE.

关键词： Object detection

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Research on Multi-view Stereo based on Depth Estimation 3

Research on Multi-view Stereo based on Depth Estimation

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Zhang, Yong Zhao, Hong School of Computer and Communication Lanzhou University of Technology Lanzhou730050 China

ISBN: (纸本)9781510667563

In deep learning-based multi-view stereo methods, the accuracy of feature extraction and the effectiveness of cost volume generation directly affect the reconstruction accuracy. To address the issues of feature extraction and depth map accuracy in current methods, this paper proposes an improved 3D reconstruction network based on a multi-scale cost volume. Firstly, in order to obtain more accurate feature information and improve feature matching, an attention module is incorporated into the feature pyramid extraction network to output three different scale feature maps, and depth estimation is performed using a coarse-to-fine cascade structure. Secondly, to alleviate the problem of over-smoothed edges caused by the regularization process due to the large receptive field and depth map upsampling, the refined upsampled depth map is guided by the feature maps of the next stage with more detailed information, thus enhancing the edge detail information of the initial depth map. Experiments on the DTU dataset show that the proposed method achieves an accuracy of 0.323mm and a completeness of 0.361mm, with a 6.2% improvement in reconstruction completeness compared to the original model, effectively improving the 3D reconstruction performance and verifying the effectiveness of the proposed method. © 2023 SPIE.

关键词： Feature extraction

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DAT-SegNet: A Medical Multi-Organ Segmentation Network Based on Deformation Attention and Transformer 3

DAT-SegNet: A Medical Multi-Organ Segmentation Network Based...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Huang, Wenxuan Liu, Chunlin Li, Ruiyi Chen, Peizhi College of Computer and Information Engineering Xiamen University Of Technology Fujian Xiamen361024 China

ISBN: (纸本)9781510667563

With the development of Transformer and its derivatives over the last two years, several research have integrated Transformer with CNN or in instead of CNN to advance medical image *** they often create acceptable feature maps for large organs, segmentation accuracy for small organs is less than satisfactory. Transformer excels at global context, but it displays limits in capturing fine-grained features, especially in medical areas, because convolution is unable to describe long-term correlations prevalent in images. This is because local information modeling lacks a spatial inductive bias. Currently available Transformer-based segmentation networks are not often optimized for this issue, we therefore use transformer as the backbone and provide a medical image segmentation network with deformation attention. The model uses attention mechanism to boost the impact of feature maps to address the issue of low accuracy of tiny organ segmentation in multi-organ segmentation tasks. On the Synapse dataset, our model has so far produced SOTA results. © 2023 SPIE.

关键词： Image segmentation

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An Improved Apriori Algorithm Based on Influence Weight 3

An Improved Apriori Algorithm Based on Influence Weight

引用

3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Zuying, Niu Gang, Fang Die, Zeng Hao, Yuan School of Electronic and Information Engineering Chongqing Three Gorges University Chongqing404020 China School of Computer Science and Engineering Chongqing Three Gorges University Chongqing404020 China

ISBN: (纸本)9781510667563

Aiming at the problems in the actual mining process of the Apriori algorithm: it does not take into account the relationship between the influence of the item, and cannot mine the association rules of some small probability events, frequently scan the database and generate a large number of candidate itemsets, an improved Apriori algorithm based on the influence weight is proposed. Firstly, according to the impact of items on affairs and the relationship between items, a weight distribution method based on item influence is used to weight items, so as to extract more hidden and valuable associated information. Secondly, in order to reduce the scanning times of the database and the overhead of I/O ports, the weight vector and compression matrix are introduced to represent the transaction database. Finally, it is compared with the classical Apriori algorithm and the Apriori algorithm based on compressed matrix. Experimental results show that the improved Apriori algorithm has higher efficiency, and can mine out frequent patterns with high influence. © 2023 SPIE.

关键词： Data mining

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Research on Global Illumination Exploration in Dynamic Scenes 3

Research on Global Illumination Exploration in Dynamic Scene...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Ji, Xiu Yang, Huamin Han, Cheng School of Computer Science and Technology Changchun University of Science and Technology Jilin Changchun130022 China School of Electrical and Information Engineering Changchun Institute of Technology Jilin Changchun130012 China

ISBN: (纸本)9781510667563

Neural rendering can achieve satisfactory illumination effects with unknown light source locations and brightness. When training on dynamic scenarios (where object positions, textures, lighting, and viewpoints can vary), variations in object position, material properties, light intensity, and angle make the training results unsatisfactory due to the influence of global light sources. This paper proposes a novel global illumination exploration method, which uses Markov Chain Monte Carlo (MCMC) to perform small sample sampling of light points, and incorporates a new Bayesian optimization (Randomized Search) strategy to optimize the sample data combined with real-time data to remove sampling redundant information and improve training efficiency. The comprehensive experimental results show that our proposed method provides a practical and effective solution for the study of global illumination in dynamic scenes. © 2023 SPIE.

关键词： Light sources

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