2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)最新文献_第3页

An optimized derivative projection warping approach for moving platform video stabilization 一种用于移动平台视频稳定的导数投影翘曲优化方法

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776218

Deepika Shukla, R. K. Jha

{"title":"An optimized derivative projection warping approach for moving platform video stabilization","authors":"Deepika Shukla, R. K. Jha","doi":"10.1109/NCVPRIPG.2013.6776218","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2013.6776218","url":null,"abstract":"This paper presents an optimized and efficient video stabilization technique based on projection curve warping. In most of the recorded videos, the relative displacement between two consecutive frames goes from 3-4 pixel for hand-held and 25-30 for moving platform applications. Based on this experimental data, the use of Sakoe-Chiba band with fixed window size has been proposed for constraining distance matrix estimation, in the dynamic time warping algorithm. In the existing projection based stabilization techniques, intensity values are matched for motion estimation. Any change in the local intensity values either induced due to intensity variation, moving objects or scene variation, causes error in the estimated motion. To overcome this problem, a higher level feature i.e. shape of the projection curve has been incorporated by matching the local derivative of curve instead of the intensity values itself. Robustness and time efficiency of the proposed technique is measured in terms of interframe transformation fidelity and processing time respectively.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125182837","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

Tracking based depth-guided video inpainting 基于跟踪的深度引导视频绘画

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776217

Saroj Hatheele, M. Zaveri

引用次数: 2

A new approach for terrain analysis of lunar surface by Chandrayaan-1 data using open source libraries 基于开源库的月船1号数据月球表面地形分析新方法

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776166

Hardik Acharya, Amitabh, T. Srinivasan, B. Gopalakrishna

引用次数: 2

Near real-time face parsing 近实时人脸分析

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776192

A. Minocha, Digvijay Singh, Nataraj Jammalamadaka, C. V. Jawahar

引用次数: 1

Time-frequency analysis based motion detection in perfusion weighted MRI 灌注加权MRI中基于时频分析的运动检测

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776215

M. Sushma, Anubha Gupta, J. Sivaswamy

{"title":"Time-frequency analysis based motion detection in perfusion weighted MRI","authors":"M. Sushma, Anubha Gupta, J. Sivaswamy","doi":"10.1109/NCVPRIPG.2013.6776215","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2013.6776215","url":null,"abstract":"In this paper, we present a novel automated method to detect motion in perfusion weighted images (PWI), which is a type of magnetic resonance imaging (MRI). In PWI, blood perfusion is measured by injecting an exogenous tracer called bolus into the blood flow of a patient and then tracking it in the brain. PWI requires a long data acquisition time to form a time series of volumes. Hence, motion occurs due to patient's unavoidable movements during a scan, which in turn results into motion corrupted data. There is a necessity of detection of these motion artifacts on captured data for correct disease diagnosis. In PWI, intensity profile gets disturbed due to occurrence of motion and/or bolus passage through the blood vessels. There is no way to distinguish between motion occurrence and bolus passage. In this paper, we propose an efficient time-frequency analysis based motion detection method. We show that proposed method is computationally inexpensive and fast. This method is evaluated on a DSC-MRI sequence with simulated motion of different degrees. We show that our approach detects motion in a few seconds.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133928361","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

Correlation based object-specific attentional mechanism for target localization in high resolution satellite images 基于相关性的高分辨率卫星图像目标定位注意机制

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776221

Phool Preet, P. Chowdhury, G. S. Malik

引用次数: 0

Single image super-resolution using compressive sensing with learned overcomplete dictionary 基于学习过完全字典的压缩感知单幅图像超分辨率

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776176

B. Deka, Kanchan Kumar Gorain, Navadeep Kalita, B. Das

引用次数: 6

Real-time approximate and exact CSG of implicit surfaces on the GPU 在GPU上实现隐式曲面的实时逼近和精确CSG

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776199

Jag Mohan Singh

{"title":"Real-time approximate and exact CSG of implicit surfaces on the GPU","authors":"Jag Mohan Singh","doi":"10.1109/NCVPRIPG.2013.6776199","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2013.6776199","url":null,"abstract":"We present a simple and powerful scheme to allow CSG of implicit surfaces on the GPU. We decompose the boolean expression of surfaces into sum-of-products form. Our algorithm presented in this paper then renders each product term, sum of products can be automatically by enabling depth test. Our Approximate CSG uses adaptive marching points algorithm for finding ray-surface intersection. Once we find an interval where root exists after root-isolation, this is used for presence of intersection. We perform root-refinement only for the uncomplemented terms in the product. Exact CSG is done by using the discriminant of the ray-surface intersection for the presence of the root. Now we can simply evaluate the product expression by checking all uncomplemented terms should be true and all complemented terms should be false. If our condition is met, we find the maximum of all the roots among uncomplemented terms to be the solution. Our algorithm is linear in the number of terms O(n). We achieve real-time rates for 4-5 terms in the product for approximate CSG. We achieve more than real-time rates for Exact CSG. Our primitives are implicit surfaces so we can achieve fairly complex results with less terms.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122552265","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

Geometric invariant Target classification using 2D Mellin cepstrum with modified grid formation 基于改进网格结构的二维Mellin倒谱几何不变目标分类

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776260

B. Sathyabama, S. Roomi, R. EvangelineJenitaKamalam

{"title":"Geometric invariant Target classification using 2D Mellin cepstrum with modified grid formation","authors":"B. Sathyabama, S. Roomi, R. EvangelineJenitaKamalam","doi":"10.1109/NCVPRIPG.2013.6776260","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2013.6776260","url":null,"abstract":"The Classification of Targets in Synthetic Aperture Radar Images is greatly affected by scale, rotation and translation. This paper proposes a geometric invariant algorithm to classify military targets based on extracting cepstral features derived from the modified grid selection over spectral components of Fourier Mellin Transform. The proposed non uniform grid is formed by a window with a cell of 2×2 pixels at the center, surrounded by the cells of 4×4 pixels, and so on, with overlapping concept to extract better representative features. Further each cell is divided into upper and lower triangular bins. The energy of each bin forms the down sampled M×M data accounting the larger value between the two triangles so that the information is enhanced. The experiments are carried out with a total of 700 SAR images collected from MSTAR database with different combinations of rotation, scale and translations. The proposed method has been tested against existing methods such as Region Covariance, Co-differencing and 2D Mellin cepstrum with non- overlapping grids. The results from 2D-Mellin Cepstrum using the proposed grid formation have been observed to be better in terms of 92% detection accuracy compared with 86% for region covariance method and 89% for non-uniform grid formation method.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124553743","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

Recognition and identification of target images using feature based retrieval in UAV missions 无人机任务中基于特征检索的目标图像识别与识别

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776165

Shweta Singh, D. V. Rao

{"title":"Recognition and identification of target images using feature based retrieval in UAV missions","authors":"Shweta Singh, D. V. Rao","doi":"10.1109/NCVPRIPG.2013.6776165","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2013.6776165","url":null,"abstract":"With the introduction of unmanned air vehicles as force multipliers in the defense services worldwide, automatic recognition and identification of ground based targets has become an important area of research in the defense community. Due to inherent instabilities in smaller unmanned platforms, image blurredness and distortion need to be addressed for the successful recognition of the target. In this paper, an image enhancement technique that can improve images' quality acquired by an unmanned system is proposed. An image de-blurring technique based on blind de-convolution algorithm which adaptively enhances the edges of characters and wipes off blurredness effectively is proposed. A content-based image retrieval technique based on features extraction to generate an image description and a compact feature vector that represents the visual information, color, texture and shape is used with a minimum distance algorithm to effectively retrieve the plausible target images from a library of images stored in a target folder. This methodology was implemented for planning and gaming the UAV/UCAV missions in the Air Warfare Simulation System.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128882269","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: 5