2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)最新文献_第4页

No-reference quality assessment for contrast-distorted image 对比度失真图像的无参考质量评价

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7820968

Jun Wu, Zhaoqiang Xia, Yifeng Ren, Huifang Li

引用次数: 8

Automatic detection, tracking and counting of birds in marine video content 海洋视频内容中鸟类的自动检测、跟踪和计数

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7821031

R. T'Jampens, F. Hernandez, F. Vandecasteele, S. Verstockt

{"title":"Automatic detection, tracking and counting of birds in marine video content","authors":"R. T'Jampens, F. Hernandez, F. Vandecasteele, S. Verstockt","doi":"10.1109/IPTA.2016.7821031","DOIUrl":"https://doi.org/10.1109/IPTA.2016.7821031","url":null,"abstract":"Robust automatic detection of moving objects in a marine context is a multi-faceted problem due to the complexity of the observed scene. The dynamic nature of the sea caused by waves, boat wakes, and weather conditions poses huge challenges for the development of a stable background model. Moreover, camera motion, reflections, lightning and illumination changes may contribute to false detections. Dynamic background subtraction (DBGS) is widely considered as a solution to tackle this issue in the scope of vessel detection for maritime traffic analysis. In this paper, the DBGS techniques suggested for ships are investigated and optimized for the monitoring and tracking of birds in marine video content. In addition to background subtraction, foreground candidates are filtered by a classifier based on their feature descriptors in order to remove non-bird objects. Different types of classifiers have been evaluated and results on a ground truth labeled dataset of challenging video fragments show similar levels of precision and recall of about 95% for the best performing classifier. The remaining foreground items are counted and birds are tracked along the video sequence using spatio-temporal motion prediction. This allows marine scientists to study the presence and behavior of birds.","PeriodicalId":123429,"journal":{"name":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122444781","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: 16

Multiple description coding based on enhanced X-tree 基于增强x树的多重描述编码

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7820953

C. Cai, J. Chen, H. Zeng

{"title":"Multiple description coding based on enhanced X-tree","authors":"C. Cai, J. Chen, H. Zeng","doi":"10.1109/IPTA.2016.7820953","DOIUrl":"https://doi.org/10.1109/IPTA.2016.7820953","url":null,"abstract":"This paper proposes a multiple description image coding scheme based on 2D dual-tree transform and the enhanced x-tree encoding method. The input image is firstly mapped into 2D dual-tree discrete wavelet domain to form 2 wavelet coefficient trees. A sparse algorithm is then used to remove the most redundant wavelet coefficients resulted from dual-tree discrete wavelet transform (DDWT), forming the basic component of both descriptions, respectively. In order to improve the quality of the side reconstruction, a side sparse algorithm is then imposed on two sparse coefficient trees to produce the additional for both side decoding. The basic information from one tree and additional information from the other are sent to an enhanced x-tree encoder, which is proposed to exploit the strong correlation between two wavelet trees resulted from DDWT, forming the bitstream of a description. Since each description includes the basic information and part of details of the input image, even one of the descriptions gets lost, the reconstructed image can still keep acceptable quality. Simulation results have verified that the proposed algorithm has good coding performance and error resilient ability.","PeriodicalId":123429,"journal":{"name":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121782114","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

On pain assessment from facial videos using spatio-temporal local descriptors 基于时空局部描述符的面部视频疼痛评估

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7820930

Ruijing Yang, Shujun Tong, Miguel Bordallo López, Elhocine Boutellaa, Jinye Peng, Xiaoyi Feng, A. Hadid

引用次数: 21

Feature covariance for human action recognition 人类动作识别的特征协方差

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7820982

Alexandre Perez, Hedi Tabia, D. Declercq, A. Zanotti

引用次数: 4

A multidimensional scaling optimization and fusion approach for the unsupervised change detection problem in remote sensing images 遥感图像无监督变化检测问题的多维尺度优化与融合方法

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7821021

Redha Touati, M. Mignotte

{"title":"A multidimensional scaling optimization and fusion approach for the unsupervised change detection problem in remote sensing images","authors":"Redha Touati, M. Mignotte","doi":"10.1109/IPTA.2016.7821021","DOIUrl":"https://doi.org/10.1109/IPTA.2016.7821021","url":null,"abstract":"It is generally well known that the overall performance of the most widely used types of unsupervised change detection methods, based on the luminance pixel-wise difference, is mainly relied on the quality of the so-called difference image and the accuracy of the classification method. In order to address these two issues, this work proposes to first estimate, a new and robust similarity feature map, playing the same role as the difference image, by specifying a set of constraints expressed for each pair of pixels existing in the multitemporal images. As a consequence, the proposed change detection method does not require any preprocessing step of the multitemporal images such as radiometric correction/normalization. In addition, input data can be acquired from different sensors. The quadratic complexity in the number of pixels of this new similarity feature map, between the multitemporal images, is reduced to a linear complexity procedure thanks to the FastMap-based optimization algorithm. Second, in order to achieve more robustness, changes are then identified, from this similarity feature map, by combining (fusing) the results of different automatic thresholding algorithms. Experimental results confirm the robustness of the proposed approach.","PeriodicalId":123429,"journal":{"name":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115399417","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

Face spoofing detection with image quality regression 基于图像质量回归的人脸欺骗检测

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7821027

Haoliang Li, Shiqi Wang, A. Kot

{"title":"Face spoofing detection with image quality regression","authors":"Haoliang Li, Shiqi Wang, A. Kot","doi":"10.1109/IPTA.2016.7821027","DOIUrl":"https://doi.org/10.1109/IPTA.2016.7821027","url":null,"abstract":"Face spoofing detection nowadays has attracted attentions regarding the biometrics authentication issue. Inspired by the observation that face spoofing detection is highly relevant with the inherent image quality which also strongly depends on the properties of the capturing devices and conditions, in this paper, we tackle the spoofing detection problem based on a two-stage learning approach. Firstly, we manually cluster the training samples based on the prior knowledge of face sample quality (e.g. camera model), and multiple quality-guided classifiers are trained based on each cluster with extracted image quality assessment (IQA) feature. Subsequently, a regression function is learned by mapping from the IQA scores to the corresponding classifier's parameters, which can be further used for classification. As such, given a new face input for verification, we can predict its classifier's coefficients based on the pre-learned regression model, with which spoofing detection can be effectively achieved. Experimental results show that we achieve significantly better classification performance compared with the strategy that directly applies the IQA features with single classifier.","PeriodicalId":123429,"journal":{"name":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122555332","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: 23

Classification of mammographic microcalcification clusters using a combination of topological and location modelling 使用拓扑和位置建模相结合的乳房x线照相微钙化簇的分类

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7820986

Oluwaseun Ashiru, R. Zwiggelaar

引用次数: 2

Automatic detection of cervical cells in Pap-smear images using polar transform and k-means segmentation 基于极坐标变换和k均值分割的巴氏涂片图像子宫颈细胞自动检测

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7821038

M. Neghina, C. Rasche, M. Ciuc, Alina Sultana, Ciprian Tiganesteanu

引用次数: 8

MCMC based sampling technique for robust multi-model fitting and visual data segmentation 基于MCMC的鲁棒多模型拟合和可视化数据分割采样技术

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2016-12-01 DOI: 10.1109/IPTA.2016.7821022

Alireza Sadri, Ruwan Tennakoon, R. Hoseinnezhad, A. Bab-Hadiashar

引用次数: 3