Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing最新文献_第10页

Don't see me, just filter me: towards secure cloud based filtering using Shamir's secret sharing and POB number system 不看我，只过滤我:使用Shamir的秘密共享和POB号码系统进行安全的基于云的过滤

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2016-12-18 DOI: 10.1145/3009977.3010036

Priyanka Singh, Nishant Agarwal, B. Raman

{"title":"Don't see me, just filter me: towards secure cloud based filtering using Shamir's secret sharing and POB number system","authors":"Priyanka Singh, Nishant Agarwal, B. Raman","doi":"10.1145/3009977.3010036","DOIUrl":"https://doi.org/10.1145/3009977.3010036","url":null,"abstract":"Cloud computing paradigm is attracting individuals as well as organizations all round the globe due to its multiple facilities of powerful resources, storage hubs, computational power and cost effective solutions. However, distributed cloud data centers pose the threat of security breaches to the privacy of the data and pose high risks. A secured image data sharing scheme over cloud domain based on the Shamir's secret sharing and permutation ordered binary number system has been proposed here. It distributes the image information into multiple random shares that reveal no information and thus can be stored securely over the distributed cloud data centers. Different image operations could be applied in the encrypted domain over the cloud servers itself. This approach reduces the threat to security which is a major hindrance in utilizing the facilities of the cloud based architecture. Only the authentic owner possessing the secret keys could restore back the original image information from the random shares. Comparative results for both the plain domain as well as the encrypted domain have been presented to validate the efficiency of using the various image filtering operations like motion blur, unsharp masking, weiner, gaussian etc in the encrypted domain over cloud.","PeriodicalId":93806,"journal":{"name":"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing","volume":"20 1","pages":"12:1-12:8"},"PeriodicalIF":0.0,"publicationDate":"2016-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86250762","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

MUSA: a banana database for ripening level determination 测定香蕉成熟程度的数据库

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2016-12-18 DOI: 10.1145/3009977.3009996

Senthilarasi M, Md Mansoor Roomi S, Sheik Naveedh A

引用次数: 1

CRF based method for curb detection using semantic cues and stereo depth 基于CRF的基于语义线索和立体深度的路边检测方法

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2016-12-18 DOI: 10.1145/3009977.3010058

Danish Sodhi, Sarthak Upadhyay, Dhaivat Bhatt, K. Krishna, S. Swarup

引用次数: 10

Exposing splicing forgeries in digital images through dichromatic plane histogram discrepancies 通过二色平面直方图差异揭露数字图像中的拼接伪造

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2016-12-18 DOI: 10.1145/3009977.3010032

A. Mazumdar, P. Bora

引用次数: 10

Learning to hash-tag videos with Tag2Vec 学习标签视频与Tag2Vec

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2016-12-13 DOI: 10.1145/3009977.3010035

A. Singh, Saurabh Saini, R. Shah, P J Narayanan

{"title":"Learning to hash-tag videos with Tag2Vec","authors":"A. Singh, Saurabh Saini, R. Shah, P J Narayanan","doi":"10.1145/3009977.3010035","DOIUrl":"https://doi.org/10.1145/3009977.3010035","url":null,"abstract":"User-given tags or labels are valuable resources for semantic understanding of visual media such as images and videos. Recently, a new type of labeling mechanism known as hash-tags have become increasingly popular on social media sites. In this paper, we study the problem of generating relevant and useful hash-tags for short video clips. Traditional data-driven approaches for tag enrichment and recommendation use direct visual similarity for label transfer and propagation. We attempt to learn a direct low-cost mapping from video to hash-tags using a two step training process. We first employ a natural language processing (NLP) technique, skip-gram models with neural network training to learn a low-dimensional vector representation of hash-tags (Tag2Vec) using a corpus of ∼ 10 million hash-tags. We then train an embedding function to map video features to the low-dimensional Tag2vec space. We learn this embedding for 29 categories of short video clips with hash-tags. A query video without any tag-information can then be directly mapped to the vector space of tags using the learned embedding and relevant tags can be found by performing a simple nearest-neighbor retrieval in the Tag2Vec space. We validate the relevance of the tags suggested by our system qualitatively and quantitatively with a user study.","PeriodicalId":93806,"journal":{"name":"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing","volume":"20 1","pages":"94:1-94:8"},"PeriodicalIF":0.0,"publicationDate":"2016-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78553642","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

Deep fusion of visual signatures for client-server facial analysis 客户端-服务器面部分析的深度融合视觉签名

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2016-11-01 DOI: 10.1145/3009977.3010062

Binod Bhattarai, Gaurav Sharma, F. Jurie

{"title":"Deep fusion of visual signatures for client-server facial analysis","authors":"Binod Bhattarai, Gaurav Sharma, F. Jurie","doi":"10.1145/3009977.3010062","DOIUrl":"https://doi.org/10.1145/3009977.3010062","url":null,"abstract":"Facial analysis is a key technology for enabling human-machine interaction. In this context, we present a client-server framework, where a client transmits the signature of a face to be analyzed to the server, and, in return, the server sends back various information describing the face e.g. is the person male or female, is she/he bald, does he have a mustache, etc. We assume that a client can compute one (or a combination) of visual features; from very simple and efficient features, like Local Binary Patterns, to more complex and computationally heavy, like Fisher Vectors and CNN based, depending on the computing resources available. The challenge addressed in this paper is to design a common universal representation such that a single merged signature is transmitted to the server, whatever be the type and number of features computed by the client, ensuring nonetheless an optimal performance. Our solution is based on learning of a common optimal subspace for aligning the different face features and merging them into a universal signature. We have validated the proposed method on the challenging CelebA dataset, on which our method outperforms existing state-of-art methods when rich representation is available at test time, while giving competitive performance when only simple signatures (like LBP) are available at test time due to resource constraints on the client.","PeriodicalId":93806,"journal":{"name":"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing","volume":"60 1","pages":"42:1-42:8"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85538317","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

Realtime motion detection based on the spatio-temporal median filter using GPU integral histograms 基于GPU积分直方图的时空中值滤波实时运动检测

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2012-12-16 DOI: 10.1145/2425333.2425352

M. Poostchi, K. Palaniappan, F. Bunyak, G. Seetharaman

{"title":"Realtime motion detection based on the spatio-temporal median filter using GPU integral histograms","authors":"M. Poostchi, K. Palaniappan, F. Bunyak, G. Seetharaman","doi":"10.1145/2425333.2425352","DOIUrl":"https://doi.org/10.1145/2425333.2425352","url":null,"abstract":"Motion detection using background modeling is a widely used technique in object tracking. To meet the demands of real-time multi-target tracking applications in large and/or high resolution imagery fast parallel algorithms for motion detection are desirable. One common method for background modeling is to use an adaptive 3D median filter that is updated appropriately based on the video sequence. We describe a parallel 3D spatiotemporal median filter algorithm implemented in CUDA for many core Graphics Processing Unit (GPU) architectures using the integral histogram as a building block to support adaptive window sizes. Both 2D and 3D median filters are also widely used in many other computer vision tasks like denoising, segmentation, and recognition. Although fast sequential median algorithms exist, improving performance using parallelization is attractive to reduce the time needed for motion detection in order to support more complex processing in multi-target tracking systems, large high resolution aerial video imagery and 3D volumetric processing. Results show the frame rate of the GPU implementation was 60 times faster than the CPU version for a 1K x 1K image reaching 49 fr/sec and 21 times faster for 512 x 512 frame sizes reaching 194 fr/sec. We characterize performance of the parallel 3D median filter for different image sizes and varying number of histogram bins and show selected results for motion detection.","PeriodicalId":93806,"journal":{"name":"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing","volume":"23 1","pages":"19"},"PeriodicalIF":0.0,"publicationDate":"2012-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73442186","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

Objective evaluation of noisy multimodal medical image fusion using Daubechies complex wavelet transform Daubechies复小波变换在多模态医学图像融合中的应用

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2012-12-16 DOI: 10.1145/2425333.2425405

Rajiv Singh, A. Khare

{"title":"Objective evaluation of noisy multimodal medical image fusion using Daubechies complex wavelet transform","authors":"Rajiv Singh, A. Khare","doi":"10.1145/2425333.2425405","DOIUrl":"https://doi.org/10.1145/2425333.2425405","url":null,"abstract":"Medical image fusion needs proper attention as images obtained from medical instruments are of poor contrast and corrupted by blur and noise due to imperfection of image capturing devices. Thus, objective evaluation of medical image fusion techniques has become an important task in noisy domain. Therefore, in the present work, we have proposed maximum selection and energy based fusion rules for the evaluation of noisy multimodal medical image fusion using Daubechies complex wavelet transform (DCxWT). Unlike, traditional real valued wavelet transforms, which suffered from shift sensitivity and did not provide any phase information, DCxWT is shift invariant and provides phase information through its imaginary coefficients. Shift invariance and availability of phase information properties of DCxWT have been found useful for fusion of multimodal medical images. The experiments have been performed over several set of noisy medical images at multiple levels of noise for the proposed fusion scheme. Further, the proposed fusion scheme has been tested up to the maximum level of Gaussian, salt & pepper and speckle noise. Objective evaluation of the proposed fusion scheme is performed with fusion factor, fusion symmetry, entropy, standard deviation and edge information metrics. Results have been shown for two sets of multimodal medical images for the proposed method with maximum and energy based fusion rules, and comparison has been done with Lifting wavelet transform (LWT) and Stationary wavelet transform (SWT) based fusion methods. Comparative analysis of the proposed method with LWT and SWT based fusion methods at different noise levels shows the superiority of the proposed scheme. Moreover, the plots of different fusion metrics against the maximum level of Gaussian, salt & pepper and speckle noise show the robustness of the proposed fusion method against noise.","PeriodicalId":93806,"journal":{"name":"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing","volume":"217 1","pages":"72"},"PeriodicalIF":0.0,"publicationDate":"2012-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74172425","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

On the use of regions for semantic image segmentation 区域在语义图像分割中的应用

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2012-12-16 DOI: 10.1145/2425333.2425384

Rui Hu, Diane Larlus, G. Csurka

引用次数: 8

Matte based generation of land cover maps 基于亚光的土地覆盖地图生成

Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing Pub Date : 2012-12-16 DOI: 10.1145/2425333.2425373

K. Bahirat, S. Chaudhuri

引用次数: 2