2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance最新文献_第7页

Real-Time Pedestrian Tracking with Bacterial Foraging Optimization 细菌觅食优化的实时行人跟踪

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.60

H. T. Nguyen, B. Bhanu

引用次数: 11

Background Subtraction for Real-Time Video Analytics Based on Multi-hypothesis Mixture-of-Gaussians 基于多假设混合高斯的实时视频分析背景减法

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.15

Mahfuzul Haque, M. Murshed

引用次数: 5

Performance Evaluation of Multi-camera Visual Tracking 多摄像机视觉跟踪的性能评价

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.86

L. Marcenaro, Pietro Morerio, C. Regazzoni

引用次数: 6

An Ensemble of Rejecting Classifiers for Anomaly Detection of Audio Events 音频事件异常检测的拒绝分类器集成

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.9

Donatello Conte, P. Foggia, G. Percannella, Alessia Saggese, M. Vento

{"title":"An Ensemble of Rejecting Classifiers for Anomaly Detection of Audio Events","authors":"Donatello Conte, P. Foggia, G. Percannella, Alessia Saggese, M. Vento","doi":"10.1109/AVSS.2012.9","DOIUrl":"https://doi.org/10.1109/AVSS.2012.9","url":null,"abstract":"Audio analytic systems are receiving an increasing interest in the scientific community, not only as stand alone systems for the automatic detection of abnormal events by the interpretation of the audio track, but also in conjunction with video analytics tools for enforcing the evidence of anomaly detection. In this paper we present an automatic recognizer of a set of abnormal audio events that works by extracting suitable features from the signals obtained by microphones installed into a surveilled area, and by classifying them using two classifiers that operate at different time resolutions. An original aspect of the proposed system is the estimation of the reliability of each response of the individual classifiers. In this way, each classifier is able to reject the samples having an overall reliability below a threshold. This approach allows our system to combine only reliable decisions, so increasing the overall performance of the method. The system has been tested on a large dataset of samples acquired from real world scenarios, the audio classes of interests are represented by gunshot, scream and glass breaking in addition to the background sounds. The preliminary results obtained encourage further research in this direction.","PeriodicalId":275325,"journal":{"name":"2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115114191","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: 41

Lightweight and Robust Shadow Removal for Foreground Detection 用于前景检测的轻量级和鲁棒阴影去除

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.44

A. Gawde, Kedar Joshi, Senem Velipasalar

引用次数: 3

Abandoned Object's Owner Detection: A Case Study of Hybrid Mobile-Fixed Video Surveillance System 基于移动-固定混合视频监控系统的遗弃物所有者检测

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.4

Minh-Son Dao, Riccardo Mattivi, F. D. Natale, Keita Masui, N. Babaguchi

引用次数: 3

Dana36: A Multi-camera Image Dataset for Object Identification in Surveillance Scenarios Dana36:用于监控场景中目标识别的多相机图像数据集

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.33

J. Pers, Vildana Sulic Kenk, Rok Mandeljc, M. Kristan, S. Kovacic

{"title":"Dana36: A Multi-camera Image Dataset for Object Identification in Surveillance Scenarios","authors":"J. Pers, Vildana Sulic Kenk, Rok Mandeljc, M. Kristan, S. Kovacic","doi":"10.1109/AVSS.2012.33","DOIUrl":"https://doi.org/10.1109/AVSS.2012.33","url":null,"abstract":"We present a novel dataset for evaluation of object matching and recognition methods in surveillance scenarios. Dataset consists of more than 23,000 images, depicting 15 persons and nine vehicles. A ground truth data - the identity of each person or vehicle - is provided, along with the coordinates of the bounding box in the full camera image. The dataset was acquired from 36 stationary camera views using a variety of surveillance cameras with resolutions ranging from standard VGA to three megapixel. 27 cameras observed the persons and vehicles in an outdoor environment, while the remaining nine observed the same persons indoors. The activity of persons was planned in advance, they drive the cars to the parking lot, exit the cars and walk around the building, through the main entrance, and up the stairs, towards the first floor of the building. The intended use of the dataset is performance evaluation of computer vision methods that aim to (re)identify people and objects from many different viewpoints in different environments and under variable conditions. Due to variety of camera locations, vantage points and resolutions, the dataset provides means to adjust the difficulty of the identification task in a controlled and documented manner. An interface for easy use of dataset within Matlab is provided as well, and the data is complemented by baseline results using a basic color histogram-based descriptor. While the cropped images of persons and vehicles represent the primary data in our dataset, we also provide full-frame images and a set of tracklets for each object as a courtesy to the dataset users.","PeriodicalId":275325,"journal":{"name":"2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121853692","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: 20

Collaborative Sparse Approximation for Multiple-Shot Across-Camera Person Re-identification 多镜头跨镜头人物再识别的协同稀疏逼近

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.21

Yang Wu, M. Minoh, M. Mukunoki, Wei Li, S. Lao

引用次数: 27

Appearance-Based Re-identification of Humans in Low-Resolution Videos Using Means of Covariance Descriptors 基于协方差描述符的低分辨率视频中人的外观再识别

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.12

J. Metzler

引用次数: 14

Semi-supervised Gait Recognition Based on Self-Training 基于自我训练的半监督步态识别

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI: 10.1109/AVSS.2012.66

Yanan Li, Yilong Yin, Lili Liu, Shaohua Pang, Qiuhong Yu

引用次数: 13