2014 IEEE International Conference on Image Processing (ICIP)最新文献_第7页

A dataset for Hand-Held Object Recognition 手持物体识别的数据集

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7026188

Jose Rivera-Rubio, Saad Idrees, I. Alexiou, Lucas Hadjilucas, A. Bharath

{"title":"A dataset for Hand-Held Object Recognition","authors":"Jose Rivera-Rubio, Saad Idrees, I. Alexiou, Lucas Hadjilucas, A. Bharath","doi":"10.1109/ICIP.2014.7026188","DOIUrl":"https://doi.org/10.1109/ICIP.2014.7026188","url":null,"abstract":"Visual object recognition is just one of the many applications of camera-equipped smartphones. The ability to recognise objects through photos taken with wearable and handheld cameras is already possible through some of the larger internet search providers; yet, there is little rigorous analysis of the quality of search results, particularly where there is great disparity in image quality. This has motivated us to develop the Small Hand-held Object Recognition Test (SHORT). This includes a dataset that is suitable for recognising hand-held objects from either snapshots or videos acquired using hand-held or wearable cameras. SHORT provides a collection of images and ground truth that help evaluate the different factors that affect recognition performance. At its present state, the dataset is comprised of a set of high quality training images and a large set of nearly 135,000 smartphone-captured test images of 30 grocery products. In this paper, we will discuss some open challenges in the visual object recognition of objects that are being held by users. We evaluate the performance of a number of popular object recognition algorithms, with differing levels of complexity, when tested against SHORT.","PeriodicalId":6856,"journal":{"name":"2014 IEEE International Conference on Image Processing (ICIP)","volume":"65 1","pages":"5881-5885"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76468036","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

Collaborative inter-prediction on CPU+GPU systems CPU+GPU系统协同互预测

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7025245

S. Momcilovic, A. Ilic, N. Roma, L. Sousa

引用次数: 4

Vanishing point estimation for challenging road images 挑战性道路图像的消失点估计

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7025200

Qingyun She, Zongqing Lu, Q. Liao

引用次数: 11

Generic segment-wise DC for 3D-HEVC depth intra coding 用于3D-HEVC深度内部编码的通用分段DC

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7025651

Hongbin Liu, Ying Chen

引用次数: 27

Retrieving images using saliency detection and graph matching 使用显著性检测和图匹配检索图像

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7025624

Shao Huang, Weiqiang Wang, Hui Zhang

引用次数: 11

Primal-dual first order methods for total variation image restoration in presence of poisson noise 泊松噪声下全变分图像恢复的原始-对偶一阶方法

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7025844

S. Bonettini, A. Benfenati, V. Ruggiero

{"title":"Primal-dual first order methods for total variation image restoration in presence of poisson noise","authors":"S. Bonettini, A. Benfenati, V. Ruggiero","doi":"10.1109/ICIP.2014.7025844","DOIUrl":"https://doi.org/10.1109/ICIP.2014.7025844","url":null,"abstract":"Image restoration often requires the minimization of a convex, possibly nonsmooth functional, given by the sum of a data fidelity measure plus a regularization term. In order to face the lack of smoothness, alternative formulations of the minimization problem could be exploited via the duality principle. Indeed, the primal-dual and the dual formulation have been well explored in the literature when the data suffer from Gaussian noise and, thus, the data fidelity term is quadratic. Unfortunately, the most part of the approaches proposed for the Gaussian are difficult to apply to general data discrepancy terms, such as the Kullback-Leibler divergence. In this work we propose primal-dual methods which apply to the minimization of the sum of general convex functions and whose iteration is easy to compute, regardless of the form of the objective function, since it essentially consists in a subgradient projection step. We provide the convergence analysis and we suggest some strategies to improve the convergence speed by means of a careful selection of the steplength parameters. A numerical experience on Total Variation based denoising and deblurring problems from Poisson data shows the behavior of the proposed method with respect to other state-of-the-art algorithms.","PeriodicalId":6856,"journal":{"name":"2014 IEEE International Conference on Image Processing (ICIP)","volume":"13 1","pages":"4156-4160"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77715713","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: 13

Who is my parent? Reconstructing video sequences from partially matching shots 谁是我的父母?从部分匹配的镜头重建视频序列

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7026081

S. Lameri, Paolo Bestagini, A. Melloni, S. Milani, A. Rocha, M. Tagliasacchi, S. Tubaro

{"title":"Who is my parent? Reconstructing video sequences from partially matching shots","authors":"S. Lameri, Paolo Bestagini, A. Melloni, S. Milani, A. Rocha, M. Tagliasacchi, S. Tubaro","doi":"10.1109/ICIP.2014.7026081","DOIUrl":"https://doi.org/10.1109/ICIP.2014.7026081","url":null,"abstract":"Nowadays, a significant fraction of the available video content is created by reusing already existing online videos. In these cases, the source video is seldom reused as is. Conversely, it is typically time clipped to extract only a subset of the original frames, and other transformations are commonly applied (e.g., cropping, logo insertion, etc.). In this paper, we analyze a pool of videos related to the same event or topic. We propose a method that aims at automatically reconstructing the content of the original source videos, i.e., the parent sequences, by splicing together sets of near-duplicate shots seemingly extracted from the same parent sequence. The result of the analysis shows how content is reused, thus revealing the intent of content creators, and enables us to reconstruct a parent sequence also when it is no longer available online. In doing so, we make use of a robust-hash algorithm that allows us to detect whether groups of frames are near-duplicates. Based on that, we developed an algorithm to automatically find near-duplicate matchings between multiple parts of multiple sequences. All the near-duplicate parts are finally temporally aligned to reconstruct the parent sequence. The proposed method is validated with both synthetic and real world datasets downloaded from YouTube.","PeriodicalId":6856,"journal":{"name":"2014 IEEE International Conference on Image Processing (ICIP)","volume":"32 1","pages":"5342-5346"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77815042","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: 22

Handwritten word spotting based on a hybrid optimal distance 基于混合最优距离的手写单词识别

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7025522

P. Wang, V. Eglin, C. Largeron, Christophe Garcia

引用次数: 1

Automatic fault tracking across seismic volumes via tracking vectors 基于跟踪向量的地震体断层自动跟踪

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7026182

Zhen Wang, Z. Long, G. Al-Regib, Asjad Amin, Mohamed Deriche

引用次数: 17

Architecture of a socio-conversational agent in virtual worlds 虚拟世界中社会会话代理的体系结构

2014 IEEE International Conference on Image Processing (ICIP) Pub Date : 2014-10-01 DOI: 10.1109/ICIP.2014.7025809

Brian Ravenet, M. Ochs, C. Pelachaud

引用次数: 0