2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)最新文献

Performance Evaluation of Optimizers for Deformable-DETR in Natural Disaster Damage Assessment 自然灾害损害评估中变形- detr优化器的性能评价

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924933

Minh Dinh, Vu L. Bui, Doanh C. Bui, Duong Phi Long, Nguyen D. Vo, Khang Nguyen

引用次数: 1

Exploiting matching local information for person re-identification 利用匹配的局部信息进行人员再识别

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924686

H. Nguyen, Hong-Quan Nguyen, Thuy-Binh Nguyen, Van-Chien Pham, Thi-Lan Le

{"title":"Exploiting matching local information for person re-identification","authors":"H. Nguyen, Hong-Quan Nguyen, Thuy-Binh Nguyen, Van-Chien Pham, Thi-Lan Le","doi":"10.1109/MAPR56351.2022.9924686","DOIUrl":"https://doi.org/10.1109/MAPR56351.2022.9924686","url":null,"abstract":"Person re-identification task with the main aim is to associate the instances of the same person captured by different cameras in a surveillance camera network usually employs the detection results. As a consequence, misalignment of detected bounding boxes and background information are the two main factors that lead to reducing the performance of person re-identification.To tackle with these challenges, the state-of-art in person re-identification methods proposed to employ attention mechanism or body parts detection. However, these methods have high complexity and computational cost, which can be reduced by using Earth Movers Distance (EMD) instead. Therefore, this paper formulates local matching as a distance calculation of two probability distributions and applies Earth Movers Distance (EMD) to compute the optimal matching between two sets of stripes in order to address an issue in the AlignedReID++ method. Different experiments have been conducted on both single-shot and multi-shot person re-identification. The obtained results have shown the improved performance of the proposed method compared with the baseline method. The matching rates at rank1 obtained by the proposed method are 49.59%, 83.36%, and 78.47% on VIPeR, Marketl501-Partial, and DukeMTMCReID-Partial, respectively.","PeriodicalId":138642,"journal":{"name":"2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121793452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vi-DRSNet: A Novel Hybrid Model for Vietnamese Image Captioning in Healthcare Domain Vi-DRSNet:一种用于医疗保健领域的越南语图像标注的新型混合模型

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924781

Doanh C. Bui, N. Nguyen, Nguyen D. Vo, Uyen Han Thuy Thai, Khang Nguyen

引用次数: 0

Researching and Implementing the Posture Recognition Algorithm of the Elderly on Jetson Nano 基于Jetson Nano的老年人姿势识别算法的研究与实现

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924968

T. Than, Duc Khanh Duy Danh, Huu Luong Nguyen, Minh-Son Nguyen

引用次数: 1

Antique Photo Restoration and Colorization via Generative Model 基于生成模型的古董照片修复与着色

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924704

Manh-Khanh Ngo Huu, V. Ngo, Thanh-Danh Nguyen, Vinh-Tiep Nguyen, T. Ngo

{"title":"Antique Photo Restoration and Colorization via Generative Model","authors":"Manh-Khanh Ngo Huu, V. Ngo, Thanh-Danh Nguyen, Vinh-Tiep Nguyen, T. Ngo","doi":"10.1109/MAPR56351.2022.9924704","DOIUrl":"https://doi.org/10.1109/MAPR56351.2022.9924704","url":null,"abstract":"In the past, many photographs of famous historical figures and moments were captured in back and white photos. Those captures are often distorted by the limitation of the old-style camera and the negative influence of the poor storing environment. It is obvious that the restoration and colorization of those images can make history lively. Since manually retouching images is time-consuming and hard to be done by people without aesthetic senses, many researchers have proposed models that automatically remove the artifacts in the old photos. However, these methods only solve either image restoration or colorization tasks which cannot fully address the task of image retouching. Consequently, in this work, we propose an effective end-to-end framework, named AIRC, for image retouching. Besides, previous works often use synthesized old photos for training but these pseudo datasets can not replicate exactly the real antique photo and prevent the trained model from being used in reality. To this end, we also introduce a new antique synthetic dataset, namely OldifiedScenes, that resembles real old photos by blending with paper and artifact textures. Quantitative and qualitative results are provided to demonstrate the effectiveness of our proposed method.","PeriodicalId":138642,"journal":{"name":"2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126963511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-quality 3D Clothing Reconstruction and Virtual-Try-On: Pants case 高品质的3D服装重建和虚拟试穿:裤子的情况下

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924990

Thanh Tuan Thai, Youngsik Yun, Heejune Ahn

引用次数: 0

Layout-invariant license plate detection and recognition 布局不变车牌检测与识别

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924802

Thi-Anh-Loan Trinh, T. Pham, Van-Dung Hoang

引用次数: 0

The Use of Machine Learning Algorithms for Evaluating Water Quality Index: A Survey and Perspective 使用机器学习算法评估水质指数:调查与展望

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924736

H. Nguyen, Tai Quang Dinh Nguyen, Hien Nguyen Thi, B. Lap, Thi-Thu-Hong Phan

引用次数: 2

An Implementation of Low-Cost Auto-Balancing Embedded System for Safety Mechanisms* 安全机构低成本自动平衡嵌入式系统的实现*

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924743

Doan Duy, B. H. Hoang, Duy Xuan Bach Nguyen, Toan Nguyen Mau

引用次数: 0

Improving the Hand Pose Estimation from Egocentric Vision via HOPE-Net and Mask R-CNN 基于HOPE-Net和Mask R-CNN的自中心视觉手部姿态估计改进

2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) Pub Date : 2022-10-01 DOI: 10.1109/MAPR56351.2022.9924768

S. Nguyen, Thi-Thu-Hong Le, Hoang-Bach Nguyen, Thanh-Tung Phan, Chi-Thanh Nguyen, Hai Vu

{"title":"Improving the Hand Pose Estimation from Egocentric Vision via HOPE-Net and Mask R-CNN","authors":"S. Nguyen, Thi-Thu-Hong Le, Hoang-Bach Nguyen, Thanh-Tung Phan, Chi-Thanh Nguyen, Hai Vu","doi":"10.1109/MAPR56351.2022.9924768","DOIUrl":"https://doi.org/10.1109/MAPR56351.2022.9924768","url":null,"abstract":"Hand pose estimation is the task of predicting the position and orientation of the hand and fingers relative to some coordinate system. It is an important task or input for applications in robotics, medical or human-computer interaction. In recent years, the success of deep convolutional neural networks and the popularity of low-cost consumer wearable cameras have made hand pose estimation on egocentric images using deep neural networks a hot topic in the computer vision field. This paper proposes a novel deep model for accurate 2D hand pose estimation that combines HOPE-Net, which estimates hand pose, and Mask R-CNN, which provides hand detection and segmentation to localize the hand in the image. First, HOPENet is used to predict the initial 2D hand pose, and the hand features are extracted from an image with a hand in the center, which is cropped from the original image based on Mask RCNN’s output. Then, we combine the initial 2D hand pose and the hand features into a fully connected layer to predict the 2D hand pose correctly. Our experiments show that the proposed model outperforms the original HOPE-Net in 2D hand pose estimation. The proposed method’s mean endpoint error (mEPE) is 48.82 pixels, while the mEPE of the 2D HOPE-Net predictor is 86.30 pixels on the First-Person Hand Action dataset.","PeriodicalId":138642,"journal":{"name":"2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134391127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0