2009 Digital Image Computing: Techniques and Applications最新文献_第4页

Incremental Object Matching with Bayesian Methods and Particle Filters 基于贝叶斯方法和粒子滤波的增量目标匹配

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.26

M. Toivanen, J. Lampinen

引用次数: 6

Real Time Target Tracking with Pan Tilt Zoom Camera 实时目标跟踪与平移倾斜变焦相机

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.84

Pankaj Kumar, A. Dick, Tan Soo Sheng

引用次数: 28

Context-Based Appearance Descriptor for 3D Human Pose Estimation from Monocular Images 基于上下文的单眼图像三维人体姿态估计描述符

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.81

S. Sedai, Bennamoun, D. Huynh

{"title":"Context-Based Appearance Descriptor for 3D Human Pose Estimation from Monocular Images","authors":"S. Sedai, Bennamoun, D. Huynh","doi":"10.1109/DICTA.2009.81","DOIUrl":"https://doi.org/10.1109/DICTA.2009.81","url":null,"abstract":"In this paper we propose a novel appearance descriptor for 3D human pose estimation from monocular images using a learning-based technique. Our image-descriptor is based on the intermediate local appearance descriptors that we design to encapsulate local appearance context and to be resilient to noise. We encode the image by the histogram of such local appearance context descriptors computed in an image to obtain the final image-descriptor for pose estimation. We name the final image-descriptor the Histogram of Local Appearance Context (HLAC). We then use Relevance Vector Machine (RVM) regression to learn the direct mapping between the proposed HLAC image-descriptor space and the 3D pose space. Given a test image, we first compute the HLAC descriptor and then input it to the trained regressor to obtain the final output pose in real time. We compared our approach with other methods using a synchronized video and 3D motion dataset. We compared our proposed HLAC image-descriptor with the Histogram of Shape Context and Histogram of SIFT like descriptors. The evaluation results show that HLAC descriptor outperforms both of them in the context of 3D Human pose estimation.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133938175","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

A Super Resolution Algorithm for Atmospherically Degraded Images Using Lucky Regions and MAP-uHMT 基于幸运区域和MAP-uHMT的大气退化图像超分辨率算法

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.94

Zhiying Wen, Feng Li, D. Fraser, A. Lambert, X. Jia

引用次数: 2

Wavelet Transform and Fusion of Linear and Non Linear Method for Face Recognition 小波变换与线性与非线性融合人脸识别方法

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.56

M. Mazloom, S. Kasaei, Nourolhoda Alemi Neissi

{"title":"Wavelet Transform and Fusion of Linear and Non Linear Method for Face Recognition","authors":"M. Mazloom, S. Kasaei, Nourolhoda Alemi Neissi","doi":"10.1109/DICTA.2009.56","DOIUrl":"https://doi.org/10.1109/DICTA.2009.56","url":null,"abstract":"This work presents a method to increase the face recognition accuracy using a combination of Wavelet, PCA, KPCA, and RBF Neural Networks. Preprocessing, feature extraction and classification rules are three crucial issues for face recognition. This paper presents a hybrid approach to employ these issues. For preprocessing and feature extraction steps, we apply a combination of wavelet transform, PCA and KPCA. During the classification stage, the Neural Network (RBF) is explored to achieve a robust decision in presence of wide facial variations. At first derives a feature vector from a set of downsampled wavelet representation of face images, then the resulting PCA-based linear features and KPCA- based nonlinear features on wavelet feature vector for reduces the dimensionary of the vector, are extracted. During the classification stage, the Neural Network (RBF) is explored to achieve a robust decision in presence of wide facial variations. The computational load of the proposed method is greatly reduced as comparing with the original PCA, KPCA, ICA and LDA based method on the ORL, Yale and AR face databases. Moreover, the accuracy of the proposed method is improved.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125639538","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: 6

A Context-Based Approach for Detecting Suspicious Behaviours 基于上下文的可疑行为检测方法

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.31

A. Wiliem, V. Madasu, W. Boles, P. Yarlagadda

{"title":"A Context-Based Approach for Detecting Suspicious Behaviours","authors":"A. Wiliem, V. Madasu, W. Boles, P. Yarlagadda","doi":"10.1109/DICTA.2009.31","DOIUrl":"https://doi.org/10.1109/DICTA.2009.31","url":null,"abstract":"A video surveillance system capable of detecting suspicious activities or behaviours is of paramount importance to law enforcement agencies. Such a system will not only reduce the work load of security personnel involved with monitoring the CCTV video feeds but also improve the time required to respond to any incident. There are two well known models to detect suspicious behaviour: misuse detection models which are dependent on suspicious behaviour definitions and anomaly detection models which measure deviations from defined normal behaviour. However, it is nearly possible to encapsulate the entire spectrum of either suspicious or normal behaviour. One of the ways to overcome this problem is by developing a system which learns in real time and adapts itself to behaviour which can be considered as common and normal or uncommon and suspicious. We present an approach utilising contextual information. Two contextual features, namely, type of behaviour and the commonality level of each type are extracted from long-term observation. Then, a data stream model which treats the incoming data as a continuous stream of information is used to extract these features. We further propose a clustering algorithm which works in conjunction with data stream model. Experiments and comparisons are conducted on the well known CAVIAR datasets to show the efficacy of utilising contextual information for detecting suspicious behaviour. The proposed approach is generic in nature and can be applicable to any features. However for the purpose of this study, we have employed pedestrian trajectories to represent the behaviour of people.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130388481","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

Texture Description in Local Scale Using Texton Histograms with Universal Dictionary 基于文本直方图和通用字典的局部尺度纹理描述

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.18

J. Rouco, M. G. Penedo, M. Ortega, A. González

引用次数: 2

A Biological Inspired Visual Landmark Recognition Architecture 生物启发的视觉地标识别体系结构

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.61

Q. Do, L. Jain

引用次数: 1

Cartoon Motion Capturing and Retargeting by Rigid Shape Manipulation 卡通动作捕捉和重定位的刚性形状操纵

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.85

Mohammad Rastegari, Mohammad Rouhani, N. Gheissari, M. Pedram

引用次数: 4

Smooth Approximation of L_infinity-Norm for Multi-view Geometry 多视图几何的l_∞-范数光滑逼近

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.64

Yuchao Dai, Hongdong Li, Mingyi He, Chunhua Shen

引用次数: 4