2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)最新文献_第2页

Point Correspondence Validation under Unknown Radial Distortion 未知径向畸变下的点对应验证

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691513

William X. Liu, Tat-Jun Chin, G. Carneiro, D. Suter

{"title":"Point Correspondence Validation under Unknown Radial Distortion","authors":"William X. Liu, Tat-Jun Chin, G. Carneiro, D. Suter","doi":"10.1109/DICTA.2013.6691513","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691513","url":null,"abstract":"Standard two-view epipolar geometry assumes that images are taken using pinhole cameras. Real cameras, however, approximate ideal pinhole cameras using lenses and apertures. This leads to radial distortion effects in images that are not characterisable by the standard epipolar geometry model. The existence of radial distortion severely impacts the efficacy of point correspondence validation based on the epipolar constraint. Many previous works deal with radial distortion by augment- ing the epipolar geometry model (with additional parameters such as distortion coefficients and centre of distortion) to enable the modelling of radial distortion effects. Indirectly, this assumes that an accurate model of the radial distortion is known. In this paper, we take a different approach: we view radial distortion as a violation to the basic epipolar geometry equation. Instead of striving to model radial distortion, we adjust the epipolar geometry to account for the distortion effects. This adjustment is performed via moving least squares (MLS) surface approxi- mation, which we extend to allow for projective estimation. We also combine M-estimators with MLS to allow robust matching of interest points under severe radial distortion. Compared to previous works, our method is much simpler and involves just solving linear subproblems. It also exhibits a higher tolerance in cases where the exact model of radial distortion is unknown.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125926002","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

Facial Expression Recognition Based on Weighted All Parts Accumulation and Optimal Expression-Specific Parts Accumulation 基于加权全部分累积和最优表情特定部分累积的面部表情识别

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691497

H. Ali, D. Powers

{"title":"Facial Expression Recognition Based on Weighted All Parts Accumulation and Optimal Expression-Specific Parts Accumulation","authors":"H. Ali, D. Powers","doi":"10.1109/DICTA.2013.6691497","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691497","url":null,"abstract":"With the increasing applications of human computer interactive systems, recognizing accurate and application oriented human expressions is becoming a challenging topic. The face is highly attractive biometric trait for expression recognition because of its physiological structure, its robustness and location. In this paper we proposed modified subspace projection method that is an extension of our previous work [11]. Our previous work was FER analysis on full face and half faces by using principal component analysis (PCA) for feature extraction. This is obviously an extension of existing PCA algorithm. In this paper PCA is applied on facial parts like left eye, right eye, nose and mouth for feature extraction. A Flow chart for the whole system is depicted in section 3. The objective of this research is to develop a more effective approach to distinguish between seven prototypic facial expressions, such as neutral, smile, anger, surprise, fear, disgust, and sadness.These techniques clearly outperform our previous paper[11]. The whole procedure is applied on Cohnkanade FEA dataset and we achieved higher accuracy than our previous method.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129796071","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

Automated Image Segmentation and Analysis of Rock Piles in an Open-Pit Mine 露天矿岩桩图像自动分割与分析

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691484

M. Thurley

引用次数: 19

Building Roof Plane Extraction from LIDAR Data 从激光雷达数据提取建筑物屋顶平面

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691490

M. Awrangjeb, Guojun Lu

{"title":"Building Roof Plane Extraction from LIDAR Data","authors":"M. Awrangjeb, Guojun Lu","doi":"10.1109/DICTA.2013.6691490","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691490","url":null,"abstract":"This paper presents a new segmentation technique to use LIDAR point cloud data for automatic extraction of building roof planes. The raw LIDAR points are first classified into two major groups: ground and non-ground points. The ground points are used to generate a 'building mask' in which the black areas represent the ground where there are no laser returns below a certain height. The non-ground points are segmented to extract the planar roof segments. First, the building mask is divided into small grid cells. The cells containing the black pixels are clustered such that each cluster represents an individual building or tree. Second, the non-ground points within a cluster are segmented based on their coplanarity and neighbourhood relations. Third, the planar segments are refined using a rule-based procedure that assigns the common points among the planar segments to the appropriate segments. Finally, another rule-based procedure is applied to remove tree planes which are generally small in size and randomly oriented. Experimental results on three Australian sites have shown that the proposed method offers high building detection and roof plane extraction rates.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122219488","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

Performance Analysis of Three Microscope Slide Scanning Techniques 三种载玻片扫描技术的性能分析

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691511

Yilun Fan, Y. Gal, A. Bradley

引用次数: 3

Closed-Loop Deep Vision 闭环深度视觉

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691492

G. Carneiro, Zhibin Liao, Tat-Jun Chin

{"title":"Closed-Loop Deep Vision","authors":"G. Carneiro, Zhibin Liao, Tat-Jun Chin","doi":"10.1109/DICTA.2013.6691492","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691492","url":null,"abstract":"There has been a resurgence of interest in one of the most fundamental aspects of computer vision, which is related to the existence of a feedback mechanism in the inference of a visual classification process. Indeed, this mechanism was present in the first computer vision methodologies, but technical and theoretical issues imposed major roadblocks that forced researchers to seek alternative approaches based on pure feed-forward inference. These open loop approaches process the input image sequentially with increasingly more complex analysis steps, and any mistake made by intermediate steps impair all subsequent analysis tasks. On the other hand, closed-loop approaches involving feed- forward and feedback mechanisms can fix mistakes made during such intermediate stages. In this paper, we present a new closed- loop inference for computer vision problems based on an iterative analysis using deep belief networks (DBN). Specifically, an image is processed using a feed-forward mechanism that will produce a classification result, which is then used to sample an image from the current belief state of the DBN. Then the difference between the input image and the sampled image is fed back to the DBN for re- classification, and this process iterates until convergence. We show that our closed-loop vision inference improves the classification results compared to pure feed-forward mechanisms on the MNIST handwritten digit dataset and the Multiple Object Categories containing shapes of horses, dragonflies, llamas and rhinos.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"233 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134356230","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: 0

Robust Ring Detection in Phase Correlation Surfaces 相位相关面鲁棒环检测

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691523

R. González

引用次数: 2

Efficient Digital FFT Convolution with Boundary Kernel Renormalisation 边界核重归一化的高效数字FFT卷积

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691496

Chris Jackett, R. Ollington, J. Lovell

引用次数: 0

A 3D Polygonal Line Chains Matching Method for Face Recognition 一种用于人脸识别的三维多边形线链匹配方法

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691471

Xun Yu, Yongsheng Gao, J. Zhou

引用次数: 0

Quality Based Frame Selection for Face Clustering in News Video 基于质量的新闻视频人脸聚类帧选择

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691517

Kaneswaran Anantharajah, S. Denman, D. Tjondronegoro, S. Sridharan, C. Fookes, Xufeng Guo

{"title":"Quality Based Frame Selection for Face Clustering in News Video","authors":"Kaneswaran Anantharajah, S. Denman, D. Tjondronegoro, S. Sridharan, C. Fookes, Xufeng Guo","doi":"10.1109/DICTA.2013.6691517","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691517","url":null,"abstract":"Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116092685","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: 12