IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision最新文献_第5页

Real-time 3D page tracking and book status recognition for high-speed book digitization based on adaptive capturing 基于自适应捕获的高速数字化图书实时三维页面跟踪与图书状态识别

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836108

Shohei Noguchi, M. Yamada, Yoshihiro Watanabe, M. Ishikawa

引用次数: 8

NRSfM using local rigidity NRSfM使用局部刚性

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836116

A. Rehan, Aamer Zaheer, Ijaz Akhter, Arfah Saeed, M. Usmani, Bilal Mahmood, Sohaib Khan

{"title":"NRSfM using local rigidity","authors":"A. Rehan, Aamer Zaheer, Ijaz Akhter, Arfah Saeed, M. Usmani, Bilal Mahmood, Sohaib Khan","doi":"10.1109/WACV.2014.6836116","DOIUrl":"https://doi.org/10.1109/WACV.2014.6836116","url":null,"abstract":"In this paper we show that typical nonrigid structure can often be approximated well as locally rigid sub-structures in time and space. Specifically, we assume that: 1) the structure can be approximated as rigid in a short local time window and 2) some point- pairs stay relatively rigid in space, maintaining a fixed distance between them during the sequence. First, we use the triangulation constraints in rigid SfM over a sliding time window to get an initial estimate of the nonrigid 3D structure. Then we automatically identify relatively rigid point-pairs in this structure, and use their length-constancy simultaneously with triangulation constraints to refine the structure estimate. Local factorization inherently handles small camera motion, short sequences and significant natural occlusions gracefully, performing better than nonrigid factorization methods. We show more stable and accurate results as compared to the state-of-the art on even short sequences starting from 15 frames only, containing camera rotations as small as 2° and up to 50% contiguous missing data.","PeriodicalId":73325,"journal":{"name":"IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision","volume":"14 1","pages":"69-74"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81993638","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: 18

Max residual classifier 最大残差分类器

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836050

H. Nguyen, Vishal M. Patel

引用次数: 4

Image segmentation of mesenchymal stem cells in diverse culturing conditions 不同培养条件下间充质干细胞的图像分割

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836058

M. J. Afridi, Chun Liu, C. Chan, S. Baek, Xiaoming Liu

{"title":"Image segmentation of mesenchymal stem cells in diverse culturing conditions","authors":"M. J. Afridi, Chun Liu, C. Chan, S. Baek, Xiaoming Liu","doi":"10.1109/WACV.2014.6836058","DOIUrl":"https://doi.org/10.1109/WACV.2014.6836058","url":null,"abstract":"Researchers in the areas of regenerative medicine and tissue engineering have great interests in understanding the relationship of different sets of culturing conditions and applied mechanical stimuli to the behavior of mesenchymal stem cells (MSCs). However, it is challenging to design a tool to perform automatic cell image analysis due to the diverse morphologies of MSCs. Therefore, as a primary step towards developing the tool, we propose a novel approach for accurate cell image segmentation. We collected three MSC datasets cultured on different surfaces and exposed to diverse mechanical stimuli. By analyzing existing approaches on our data, we choose to substantially extend binarization-based extraction of alignment score (BEAS) approach by extracting novel discriminating features and developing an adaptive threshold estimation model. Experimental results on our data shows our approach is superior to seven conventional techniques. We also define three quantitative measures to analyze the characteristics of images in our datasets. To the best of our knowledge, this is the first study that applied automatic segmentation to live MSC cultured on different surfaces with applied stimuli.","PeriodicalId":73325,"journal":{"name":"IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision","volume":"55 1","pages":"516-523"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89194629","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

Video segmentation with joint object and trajectory labeling 结合目标和轨迹标记的视频分割

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836017

M. Yang, B. Rosenhahn

引用次数: 3

Consensus-based matching and tracking of keypoints for object tracking 基于共识的目标跟踪关键点匹配与跟踪

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836013

G. Nebehay, R. Pflugfelder

{"title":"Consensus-based matching and tracking of keypoints for object tracking","authors":"G. Nebehay, R. Pflugfelder","doi":"10.1109/WACV.2014.6836013","DOIUrl":"https://doi.org/10.1109/WACV.2014.6836013","url":null,"abstract":"We propose a novel keypoint-based method for long-term model-free object tracking in a combined matching-and-tracking framework. In order to localise the object in every frame, each keypoint casts votes for the object center. As erroneous keypoints are hard to avoid, we employ a novel consensus-based scheme for outlier detection in the voting behaviour. To make this approach computationally feasible, we propose not to employ an accumulator space for votes, but rather to cluster votes directly in the image space. By transforming votes based on the current keypoint constellation, we account for changes of the object in scale and rotation. In contrast to competing approaches, we refrain from updating the appearance information, thus avoiding the danger of making errors. The use of fast keypoint detectors and binary descriptors allows for our implementation to run in real-time. We demonstrate experimentally on a diverse dataset that is as large as 60 sequences that our method outperforms the state-of-the-art when high accuracy is required and visualise these results by employing a variant of success plots.","PeriodicalId":73325,"journal":{"name":"IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision","volume":"2 1","pages":"862-869"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88963142","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: 166

System for semi-automated surveying of street-lighting poles from street-level panoramic images 从街道全景图像半自动测量街道灯杆的系统

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836109

L. Hazelhoff, Ivo M. Creusen, P. D. With

{"title":"System for semi-automated surveying of street-lighting poles from street-level panoramic images","authors":"L. Hazelhoff, Ivo M. Creusen, P. D. With","doi":"10.1109/WACV.2014.6836109","DOIUrl":"https://doi.org/10.1109/WACV.2014.6836109","url":null,"abstract":"Accurate and up-to-date inventories of lighting poles are of interest to energy companies, beneficial for the transition to energy-efficient lighting and may contribute to a more adequate lighting of streets. This potentially improves social security and reduces crime and vandalism during nighttime. This paper describes a system for automated surveying of lighting poles from street-level panoramic images. The system consists of two independent detectors, focusing at the detection of the pole itself and at the detection of a specific lighting fixture type. Both follow the same approach, and start with detection of the feature of interest (pole or fixture) within the individual images, followed by a multi-view analysis to retrieve the real-world coordinates of the poles. Afterwards, the detection output of both algorithms is merged. Large-scale validations, covering about 135 km of road, show that over 91% of the lighting poles is found, while the precision remains above 50%. When applying this system in a semi-automated fashion, high-quality inventories can be created up to 5 times more efficiently compared to manually surveying all poles from the images.","PeriodicalId":73325,"journal":{"name":"IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision","volume":"120 1","pages":"129-136"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86167045","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: 4

A joint perspective towards image super-resolution: Unifying external- and self-examples 图像超分辨的联合视角:外部与自身实例的统一

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836048

Zhangyang Wang, Zhaowen Wang, Shiyu Chang, Jianchao Yang, Thomas S. Huang

引用次数: 9

Data association based ant tracking with interactive error correction 基于数据关联的交互式纠错蚁群跟踪

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836003

Hoan Nguyen, Thomas Fasciano, D. Charbonneau, A. Dornhaus, M. Shin

引用次数: 6

A spatial-color layout feature for representing galaxy images 用于表示星系图像的空间颜色布局特性

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision Pub Date : 2014-03-24 DOI: 10.1109/WACV.2014.6836098

Yin Cui, Yongzhou Xiang, Kun Rong, R. Feris, Liangliang Cao

{"title":"A spatial-color layout feature for representing galaxy images","authors":"Yin Cui, Yongzhou Xiang, Kun Rong, R. Feris, Liangliang Cao","doi":"10.1109/WACV.2014.6836098","DOIUrl":"https://doi.org/10.1109/WACV.2014.6836098","url":null,"abstract":"We propose a spatial-color layout feature specially designed for galaxy images. Inspired by findings on galaxy formation and evolution from Astronomy, the proposed feature captures both global and local morphological information of galaxies. In addition, our feature is scale and rotation invariant. By developing a hashing-based approach with the proposed feature, we implemented an efficient galaxy image retrieval system on a dataset with more than 280 thousand galaxy images from the Sloan Digital Sky Survey project. Given a query image, the proposed system can rank-order all galaxies from the dataset according to relevance in only 35 milliseconds on a single PC. To the best of our knowledge, this is one of the first works on galaxy-specific feature design and large-scale galaxy image retrieval. We evaluated the performance of the proposed feature and the galaxy image retrieval system using web user annotations, showing that the proposed feature outperforms other classic features, including HOG, Gist, LBP, and Color-histograms. The success of our retrieval system demonstrates the advantages of leveraging computer vision techniques in Astronomy problems.","PeriodicalId":73325,"journal":{"name":"IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision","volume":"66 1","pages":"213-219"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91133205","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