2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)最新文献_第2页

Adaptive Random Testing for Image Comparison in Regression Web Testing 回归网页测试中图像比较的自适应随机测试

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008093

Elmin Selay, Z. Zhou, Jingjie Zou

引用次数: 18

Data-Driven Street Scene Layout Estimation for Distant Object Detection 远距离目标检测的数据驱动街景布局估计

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008099

Donghao Zhang, Xuming He, Hanxi Li

引用次数: 6

Affinity Pansharpening and Image Fusion 亲和性泛锐化和图像融合

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008094

Stephen Tierney, Junbin Gao, Yi Guo

引用次数: 13

Establishing Correspondences between Planar Image Patches 建立平面图像块间的对应关系

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008107

A. Tanács, A. Majdik, József Molnár, A. Rai, Z. Kato

{"title":"Establishing Correspondences between Planar Image Patches","authors":"A. Tanács, A. Majdik, József Molnár, A. Rai, Z. Kato","doi":"10.1109/DICTA.2014.7008107","DOIUrl":"https://doi.org/10.1109/DICTA.2014.7008107","url":null,"abstract":"Finding correspondences between image pairs is a fundamental task in computer vision. Herein, we focus on establishing matches between images of urban scenes which are typically composed of planar surface patches with highly repetitive structures. The latter property makes traditional point-based methods unreliable. The basic idea of our approach is to formulate the correspondence problem in terms of homography estimation between planar image regions: given a planar region in one image, we are simultaneously looking for its corresponding segmentation in the other image and the planar homography acting between the two regions. We will show, that due to the overlapping views the general 8 degree of freedom (DOF) of the homography mapping can be geometrically constrained to 3 DOF and the resulting segmentation/registration problem can be efficiently solved by finding the region's occurrence in the second image using pyramid representation and normalized mutual information as the intensity similarity measure. The method has been validated on a large database of building images taken by different mobile cameras and quantitative evaluation confirms robustness against intensity variations, occlusions or the presence of non-planar parts. We also show examples of 3D planar surface reconstruction as well as 2D mosaicking.","PeriodicalId":146695,"journal":{"name":"2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127743722","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: 8

A Novel Landmark Detector System for Multi Resolution Frontal Faces 一种新的多分辨率正面地标检测系统

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008089

A. Liang, Chenyu Wang, Wanquan Liu, Ling Li

{"title":"A Novel Landmark Detector System for Multi Resolution Frontal Faces","authors":"A. Liang, Chenyu Wang, Wanquan Liu, Ling Li","doi":"10.1109/DICTA.2014.7008089","DOIUrl":"https://doi.org/10.1109/DICTA.2014.7008089","url":null,"abstract":"In this paper, we implement a facial landmarking system to improve the performance of landmark location accuracy for the tree-structured based facial detector proposed recently by Zhu and Ramanan. Our main objective is to overcome their limitation where very small faces could not be detected and landmarked. Furthermore, we also want to improve the landmarking accuracy and reduce false positive rate for facial images with various resolutions in one image. We achieve these aims by developing two separate tree-structured face models in an integrated system. The first one is the Multi Resolution (MR) models where it can detect faces on images of any resolution and further provide suitable number of landmarks. The second one is that we develop a Tree-structured Filter Model (TFM) which can reduce false positives quickly to avoid high processing time for multiple faces with different resolutions in one image. Finally, we combine these 2 models with Viola-Jones face detector to create a facial landmarking system. Our experiments show that our proposed models can detect small faces down to 30x30 pixels. Furthermore, our models can improve the landmarking accuracy as well as reduce false positive rates significantly.","PeriodicalId":146695,"journal":{"name":"2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132675943","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

Probabilistic Detection of Crowd Events on Riemannian Manifolds 黎曼流形上人群事件的概率检测

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008124

A. S. Rao, J. Gubbi, S. Marusic, M. Palaniswami

{"title":"Probabilistic Detection of Crowd Events on Riemannian Manifolds","authors":"A. S. Rao, J. Gubbi, S. Marusic, M. Palaniswami","doi":"10.1109/DICTA.2014.7008124","DOIUrl":"https://doi.org/10.1109/DICTA.2014.7008124","url":null,"abstract":"Event detection in crowded scenarios becomes complex due to articulated human movements, occlusions and complexities involved in tracking individual humans. In this work, we focus on crowd event (activity) detection and classification. We focus on active crowd (continuously moving crowd) events. First, event primitives such as motion, action, activity and behaviour are defined. Furthermore, a distinction is made among event detection, action recognition and abnormal event detection. Further, event detection and classification are defined on Riemannian Manifolds that yields six different probabilities of the event occurring. Using a new probabilistic approach, an automated event detection algorithm is proposed that temporally segments the event using a novel framework. The results indicate that the proposed approach delivers superior performance in selected cases and similar results in other cases, whilst the detection model delay allows operation in near real-time. The Performance Evaluation of Tracking and Surveillance (PETS) 2009 dataset was used for evaluation. Existing crowd event detection approaches used supervised approach, whereas we eschew semi-supervised approach.","PeriodicalId":146695,"journal":{"name":"2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134268209","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

Quantization Based Watermarking Approach with Gain Attack Recovery 基于量化的增益攻击恢复水印方法

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008125

Y. Zolotavkin, M. Juhola

引用次数: 1

Discriminative Key Pose Extraction Using Extended LC-KSVD for Action Recognition 基于扩展LC-KSVD的判别键姿态提取用于动作识别

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008101

Lijuan Zhou, W. Li, Yuyao Zhang, P. Ogunbona, D. Nguyen, Hanling Zhang

引用次数: 77

Effect of Smoothing on Sparsity Prior CT Reconstruction 平滑对稀疏度先验CT重建的影响

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008104

Sajib Saha, M. Tahtali, A. Lambert, M. Pickering

引用次数: 2

3D Reconstruction of Planar Patches Seen by Omnidirectional Cameras 全向相机观测平面斑块的三维重建

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2014-11-01 DOI: 10.1109/DICTA.2014.7008081

József Molnár, Robert Frohlich, D. Chetverikov, Z. Kato

引用次数: 7