2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)最新文献_第6页

Sparse Variation Pattern for Texture Classification 纹理分类的稀疏变化模式

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691530

M. Tavakolian, F. Hajati, A. Mian, S. Gheisari

引用次数: 1

Person Re-Identification Using Group Information 使用组信息重新识别人员

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-11-28 DOI: 10.1109/DICTA.2013.6691512

Alina Bialkowski, P. Lucey, Xinyu Wei, S. Sridharan

{"title":"Person Re-Identification Using Group Information","authors":"Alina Bialkowski, P. Lucey, Xinyu Wei, S. Sridharan","doi":"10.1109/DICTA.2013.6691512","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691512","url":null,"abstract":"After first observing a person, the task of person re-identification involves recognising an individual at different locations across a network of cameras at a later time. Traditionally, this task has been performed by first extracting appearance features of an individual and then matching these features to the previous observation. However, identifying an individual based solely on appearance can be ambiguous, particularly when people wear similar clothing (i.e. people dressed in uniforms in sporting and school settings). This task is made more difficult when the resolution of the input image is small as is typically the case in multi-camera networks. To circumvent these issues, we need to use other contextual cues. In this paper, we use \"group\" information as our contextual feature to aid in the re-identification of a person, which is heavily motivated by the fact that people generally move together as a collective group. To encode group context, we learn a linear mapping function to assign each person to a \"role\" or position within the group structure. We then combine the appearance and group context cues using a weighted summation. We demonstrate how this improves performance of person re-identification in a sports environment over appearance based-features.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132348144","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: 19

Using Super-Resolution Methods to Solve a Novel Multi-Sinusoidal Signal Model 用超分辨率方法求解一种新型多正弦信号模型

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-11-01 DOI: 10.1109/DICTA.2013.6691537

R. Marchant, P. Jackway

引用次数: 3

Utilizing Least Significant Bit-Planes of RONI Pixels for Medical Image Watermarking 利用RONI像素的最低有效位平面进行医学图像水印

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-11-01 DOI: 10.1109/DICTA.2013.6691538

H. Nyeem, W. Boles, C. Boyd

{"title":"Utilizing Least Significant Bit-Planes of RONI Pixels for Medical Image Watermarking","authors":"H. Nyeem, W. Boles, C. Boyd","doi":"10.1109/DICTA.2013.6691538","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691538","url":null,"abstract":"We propose a computationally efficient image border pixel based watermark embedding scheme for medical images. We considered the border pixels of a medical image as RONI (region of non-interest), since those pixels have no or little interest to doctors and medical professionals irrespective of the image modalities. Although RONI is used for embedding, our proposed scheme still keeps distortion at a minimum level in the embedding region using the optimum number of least significant bit-planes for the border pixels. All these not only ensure that a watermarked image is safe for diagnosis, but also help minimize the legal and ethical concerns of altering all pixels of medical images in any manner (e.g, reversible or irreversible). The proposed scheme avoids the need for RONI segmentation, which incurs capacity and computational overheads. The performance of the proposed scheme has been compared with a relevant scheme in terms of embedding capacity, image perceptual quality (measured by SSIM and PSNR), and computational efficiency. Our experimental results show that the proposed scheme is computationally efficient, offers an image-content-independent embedding capacity, and maintains a good image quality of RONI while keeping all other pixels in the image untouched.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123582493","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: 36

ICFSIFT: Improving Collection-Specific CBIR with ICF-Based Local Features ICFSIFT:利用基于icf的局部特征改进采集特异性CBIR

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-11-01 DOI: 10.1109/DICTA.2013.6691498

Nabeel Mohammed, D. Squire

引用次数: 1

On the Effect of Human Body Parts in Large Scale Human Behaviour Recognition 人体部位在大规模人体行为识别中的作用研究

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-11-01 DOI: 10.1109/DICTA.2013.6691507

O. V. R. Murthy, Ibrahim Radwan, Abhinav Dhall, Roland Göcke

{"title":"On the Effect of Human Body Parts in Large Scale Human Behaviour Recognition","authors":"O. V. R. Murthy, Ibrahim Radwan, Abhinav Dhall, Roland Göcke","doi":"10.1109/DICTA.2013.6691507","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691507","url":null,"abstract":"Automatic analysis of human behaviour in large collections of videos is gaining interest, even more so with the advent of file sharing sites such as YouTube. Human behaviour analysis methods can be categorised into three classes based on the type of features. The three representations are local, region of interest and densely sampled based representations. Local feature representation, such as Spatio-Temporal Interest Points (STIP), are quite popular for modelling temporal aspects in human action recognition. Region of Interest (ROI) based feature representations try to capture and represent human body part regions. Densely sampled representations capture information at uniformly spaced intervals spread in space and temporal directions of the given video. In this paper, we investigate the effect of human body part (ROI) information in large scale action recognition. Further, we also investigate the effect of its fusion with Harris 3D points (local representation) information and densely sampled representations. All experiments use a Bag-of-Words framework. We present our results on large class benchmark databases such as the UCF50 and HMDB51 datasets.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116352025","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: 3

Pathological Gait Detection of Parkinson's Disease Using Sparse Representation 基于稀疏表示的帕金森病病理步态检测

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-11-01 DOI: 10.1109/DICTA.2013.6691510

Yuyao Zhang, P. Ogunbona, W. Li, B. Munro, G. Wallace

{"title":"Pathological Gait Detection of Parkinson's Disease Using Sparse Representation","authors":"Yuyao Zhang, P. Ogunbona, W. Li, B. Munro, G. Wallace","doi":"10.1109/DICTA.2013.6691510","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691510","url":null,"abstract":"Parkinson's disease is a progressively degenerative neurological disorder which impacts the control of body movements. While there is no known permanent cure for the disorder, it is possible to monitor the progression and establish management regime that could help the medical team, patients and their family cope with the condition. Gait analysis becomes an attractive quantitative and non-invasive mechanism that can aid early detection and monitoring of the response of patients to the management schedules. In this paper, we model cycles of human gait as a sparsely represented signal using over-complete dictionary. This representation forms the basis of a classification that allows the recognition of symptomatic subjects. Experiments have been conducted using signals of vertical ground reaction force (GRF) from subjects with Parkinson's disease from the publicly available gait database (physionet.org). Our method achieved a classification accuracy of 83% in recognising pathological cases and represents a significant improvement on previously published results that use a selection of the Fourier transform coefficients as features.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128636966","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: 22

Combining Multiple Manifold-Valued Descriptors for Improved Object Recognition 结合多个流形值描述符改进目标识别

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-11-01 DOI: 10.1109/DICTA.2013.6691493

Sadeep Jayasumana, R. Hartley, M. Salzmann, Hongdong Li, M. Harandi

引用次数: 25

Parallel Implementation of Geodesic Distance Transform with Application in Superpixel Segmentation 测地线距离变换的并行实现及其在超像素分割中的应用

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-11-01 DOI: 10.1109/DICTA.2013.6691508

Tuan Q. Pham

引用次数: 8

Soil Biochar Quantification via Hyperspectral Unmixing 土壤生物炭的高光谱分解定量研究

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-11-01 DOI: 10.1109/DICTA.2013.6691529

Lei Tong, J. Zhou, Chengyuan Xu, Y. Qian, Yongsheng Gao

引用次数: 3