2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)最新文献_第7页

Helicobacter Pylori Classification based on Deep Neural Network 基于深度神经网络的幽门螺杆菌分类

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909848

Yu-Wen Lin, Guo-Shiang Lin, S. Chai

引用次数: 5

A New Bayesian Modeling for 3D Human-Object Action Recognition 一种新的三维人-物动作识别贝叶斯模型

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909873

Camille Maurice, Francisco Madrigal, A. Monin, F. Lerasle

引用次数: 4

3DMA: A Multi-modality 3D Mask Face Anti-spoofing Database 3DMA:一个多模态3D面具人脸防欺骗数据库

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909845

Jinchuan Xiao, Yinhang Tang, Jianzhu Guo, Yang Yang, Xiangyu Zhu, Zhen Lei, Stan Z. Li

{"title":"3DMA: A Multi-modality 3D Mask Face Anti-spoofing Database","authors":"Jinchuan Xiao, Yinhang Tang, Jianzhu Guo, Yang Yang, Xiangyu Zhu, Zhen Lei, Stan Z. Li","doi":"10.1109/AVSS.2019.8909845","DOIUrl":"https://doi.org/10.1109/AVSS.2019.8909845","url":null,"abstract":"Benefiting from publicly available databases, face anti-spoofing has recently gained extensive attention in the academic community. However, most of the existing databases focus on the 2D object attacks, including photo and video attacks. The only two public 3D mask face anti-spoofing database are very small. In this paper, we release a multi-modality 3D mask face anti-spoofing database named 3DMA, which contains 920 videos of 67 genuine subjects wearing 48 kinds of 3D masks, captured in visual (VIS) and near-infrared (NIR) modalities. To simulate the real world scenarios, two illumination and four capturing distance settings are deployed during the collection process. To the best of our knowledge, the proposed database is currently the most extensive public database for 3D mask face anti-spoofing. Furthermore, we build three protocols for performance evaluation under different illumination conditions and distances. Experimental results with Convolutional Neural Network (CNN) and LBP-based methods reveal that our proposed 3DMA is indeed a challenge for face anti-spoofing. This database is available at http://www.cbsr.ia.ac.cn/english/3DMA.html. We hope our public 3DMA database can help to pave the way for further research on 3D mask face anti-spoofing.","PeriodicalId":243194,"journal":{"name":"2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127876203","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: 7

Multi-Threshold based Ground Detection for Point Cloud Scene 基于多阈值的点云场景地面检测

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909897

Chien-Chou Lin, Chih-Wei Lee, L. Yao

引用次数: 2

Vehicle Tracking Using Deep SORT with Low Confidence Track Filtering 基于低置信度跟踪滤波的深度排序车辆跟踪

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909903

Xinyu Hou, Yi Wang, Lap-Pui Chau

引用次数: 66

RGB-Depth Cross-Modal Person Re-identification rgb -深度跨模态人员再识别

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909838

Frank M. Hafner, Amran Bhuiyan, Julian F. P. Kooij, Eric Granger

{"title":"RGB-Depth Cross-Modal Person Re-identification","authors":"Frank M. Hafner, Amran Bhuiyan, Julian F. P. Kooij, Eric Granger","doi":"10.1109/AVSS.2019.8909838","DOIUrl":"https://doi.org/10.1109/AVSS.2019.8909838","url":null,"abstract":"Person re-identification is a key challenge for surveillance across multiple sensors. Prompted by the advent of powerful deep learning models for visual recognition, and inexpensive RGBD cameras and sensor-rich mobile robotic platforms, e.g. self-driving vehicles, we investigate the relatively unexplored problem of cross-modal re-identification of persons between RGB (color) and depth images. The considerable divergence in data distributions across different sensor modalities introduces additional challenges to the typical difficulties like distinct viewpoints, occlusions, and pose and illumination variation. While some work has investigated re-identification across RGB and infrared, we take inspiration from successes in transfer learning from RGB to depth in object detection tasks. Our main contribution is a novel cross-modal distillation network for robust person re-identification, which learns a shared feature representation space of person's appearance in both RGB and depth images. The proposed network was compared to conventional and deep learning approaches proposed for other cross-domain re-identification tasks. Results obtained on the public BIWI and RobotPKU datasets indicate that the proposed method can significantly outperform the state-of-the-art approaches by up to 10.5% mAp, demonstrating the benefit of the proposed distillation paradigm.","PeriodicalId":243194,"journal":{"name":"2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115511250","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: 9

Joint Coarse-and-Fine Semantic Segmentation 联合粗精语义分割

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909829

Yi-Cheng Chiu, Chih-Yang Lin, T. Shih

引用次数: 0

A Comprehensive Study on Large-Scale Person Retrieval in Real Surveillance Scenarios 真实监控场景下大规模人员检索的综合研究

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909851

Da Li, Zhang Zhang, Caifeng Shan, Liang Wang, T. Tan

{"title":"A Comprehensive Study on Large-Scale Person Retrieval in Real Surveillance Scenarios","authors":"Da Li, Zhang Zhang, Caifeng Shan, Liang Wang, T. Tan","doi":"10.1109/AVSS.2019.8909851","DOIUrl":"https://doi.org/10.1109/AVSS.2019.8909851","url":null,"abstract":"Person retrieval is a hot research topic due to its important application potential for public security. Though existing algorithms have achieved impressive progresses on current public datasets, it is still a challenging task in the real surveillance scenarios due to the various viewpoints, pose variations and occlusions. Moreover, few of the existing works study the problem of person retrieval on large-scale gallery set, where lots of distractions may deteriorate the retrieval results heavily. To have a deep understanding on the above challenges, we perform a comprehensive study on current state-of-the-art person retrieval algorithms with a large-scale benchmark in real surveillance scenarios. In the study, two kinds of techniques, i.e., attribute recognition and person re-identification, including eight algorithms, are evaluated at both algorithm level and system level. Here, the system-level evaluations investigate the effects of the combinations of the above algorithms with the module of person detection, where lots of distractions in person detection results pose a big challenge for person retrieval in real scenes. Extensive evaluations with large gallery sizes (up to 243k) and comprehensive analyses are presented in the study, which will guide researchers to develop more advanced algorithms in future.","PeriodicalId":243194,"journal":{"name":"2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134404392","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: 1

Spatial Attention for Pedestrian Detection 行人检测中的空间注意

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909907

Ujjwal, Aziz Dziri, Bertrand Leroy, F. Brémond

引用次数: 1

Suggesting Gaze-based Selection for Surveillance Applications 建议基于注视的监视应用选择

2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2019-09-01 DOI: 10.1109/AVSS.2019.8909833

Jutta Hild, E. Peinsipp-Byma, M. Voit, J. Beyerer

{"title":"Suggesting Gaze-based Selection for Surveillance Applications","authors":"Jutta Hild, E. Peinsipp-Byma, M. Voit, J. Beyerer","doi":"10.1109/AVSS.2019.8909833","DOIUrl":"https://doi.org/10.1109/AVSS.2019.8909833","url":null,"abstract":"The selection operation is a basic input operation when interacting with a computer. Traditional manual selection methods like mouse input are challenging when interacting with a dynamic scene containing moving objects as it occurs in surveillance applications. In this contribution, we give an overview on gaze-based selection as a fast and intuitive alternative method considering typical selection tasks in surveillance applications. In this context, we report the results of an evaluation on initialization of an object-tracking algorithm performed by eighteen expert video analysts. Besides its benefits, gaze-based selection is difficult if selection objects are small and close together. We provide first results of a pilot study evaluating a distance measure, which might have the potential of making gaze-based selection more robust. Finally, to leverage gaze-based selection becoming a common technique, low-cost eye-tracking devices have to be available which achieve the same accuracy as the high-end devices. As such cheap eye-trackers only recently became available, it is so far not evident, which accuracy we can expect. Hence, we report the results of an accuracy evaluation of the Tobii 4C conducted with twelve students performing a calibration-style task.","PeriodicalId":243194,"journal":{"name":"2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125556307","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: 5