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2014 5th European Workshop on Visual Information Processing (EUVIP)最新文献

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Evolutionary feature synthesis by multi-dimensional particle swarm optimization 基于多维粒子群优化的进化特征合成
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018364
Jenni Raitoharju, S. Kiranyaz, M. Gabbouj
{"title":"Evolutionary feature synthesis by multi-dimensional particle swarm optimization","authors":"Jenni Raitoharju, S. Kiranyaz, M. Gabbouj","doi":"10.1109/EUVIP.2014.7018364","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018364","url":null,"abstract":"Several existing content-based image retrieval and classification systems rely on low-level features which are automatically extracted from images. However, often these features lack the discrimination power needed for accurate description of the image content and hence they may lead to a poor retrieval or classification performance. This article applies an evolutionary feature synthesis method based on multi-dimensional particle swarm optimization on low-level image features to enhance their discrimination ability. The proposed method can be applied on any database and low-level features as long as some ground-truth information is available. Content-based image retrieval experiments show that a significant performance improvement can be achieved.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123011080","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
Objective keyword selection for lecture video annotation 目的:讲座视频标注关键词选择
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018378
Ali Shariq Imran, Laksmita Rahadianti, F. A. Cheikh, Sule YAYILGAN YILDIRIM
{"title":"Objective keyword selection for lecture video annotation","authors":"Ali Shariq Imran, Laksmita Rahadianti, F. A. Cheikh, Sule YAYILGAN YILDIRIM","doi":"10.1109/EUVIP.2014.7018378","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018378","url":null,"abstract":"This paper presents an objective keyword selection method called visualness with Lesk disambiguation (VLD) for describing educational videos with semantic tags. It extends the work on automatically extracting and associating meaningful keywords carried out in `semantic tags for lecture videos' for efficient indexing and retrieval. VLD uses lecture videos and surrogates documents such as lecture transcripts to extract potential candidate keywords. The candidate keywords undergo a series of selection process extracting fewer but more meaningful keywords based on word sense disambiguation (WSD) and visual similarity. The objective metric then selects top ranking keywords by employing a rank cut-off method. The proposed metric is validated by comparing the automatically selected keywords to those obtained manually, suggesting that the words selected by the proposed objective metric correlate highly with those selected by viewers. The results are further compared to traditional term frequency inverse document frequency (TF-IDF) and state-of-the-art latent Dirichlet allocation (LDA) method, with an improved accuracy of 68.18% on 30 lecture videos.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"411 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126688904","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
Trajectory feature fusion for human action recognition 基于轨迹特征融合的人体动作识别
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018409
S. Megrhi, Azeddine Beghdadi, W. Souidène
{"title":"Trajectory feature fusion for human action recognition","authors":"S. Megrhi, Azeddine Beghdadi, W. Souidène","doi":"10.1109/EUVIP.2014.7018409","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018409","url":null,"abstract":"This paper addresses the problem of human action detection/recognition by investigating interest points (IP) trajectory cues and by reducing undesirable small camera motion. We first detect speed up robust feature (SURF) to segment video into frame volume (FV) that contains small actions. This segmentation relies on IP trajectory tracking. Then, for each FV, we extract optical flow of every detected SURF. Finally, a parametrization of the optical flow leads to displacement segments. These features are concatenated into a trajectory feature in order to describe the trajectory of IP upon a FV. We reduce the impact of camera motion by considering moving IPs beyond a minimum motion angle and by using motion boundary histogram (MBH). Feature-fusion based action recognition is performed to generate robust and discriminative codebook using K-mean clustering. We employ a bag-of-visual-words Support Vector Machine (SVM) approach for the learning /testing step. Through an extensive experimental evaluation carried out on the challenging UCF sports datasets, we show the efficiency of the proposed method by achieving 83.5% of accuracy.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124339475","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
Correspondence matching based on Higher Order Statistics for Multi-view plus Depth video sequences 基于高阶统计量的多视点加深度视频序列对应匹配
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018404
S. Colonnese, P. Oliveira, A. Rosato, L. Ungaro, Azeddine Beghdadi, M. Biagi, G. Scarano
{"title":"Correspondence matching based on Higher Order Statistics for Multi-view plus Depth video sequences","authors":"S. Colonnese, P. Oliveira, A. Rosato, L. Ungaro, Azeddine Beghdadi, M. Biagi, G. Scarano","doi":"10.1109/EUVIP.2014.7018404","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018404","url":null,"abstract":"This work addresses the problem of correspondence matching in multiview video sequences when co-acquired depth maps are available, as in the novel Multiview Video plus Depth (MVD) format. For the purpose of activity-based correspondence matching, we exploit the view depth information, allowing a thorough geometrical analysis of the video scene, and the statistical analysis of the inter-frame differences.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"107 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120870988","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
Image processing and classification in diabetic retinopathy: A review 糖尿病视网膜病变的图像处理与分类研究进展
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018362
A. Ahmad, A. Mansoor, R. Mumtaz, Mukaram Khan, S. H. Mirza
{"title":"Image processing and classification in diabetic retinopathy: A review","authors":"A. Ahmad, A. Mansoor, R. Mumtaz, Mukaram Khan, S. H. Mirza","doi":"10.1109/EUVIP.2014.7018362","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018362","url":null,"abstract":"Diabetic retinopathy is one of the disabling microvascular complications of diabetes mellitus that causes the loss of central vision or in cases complete vision loss if not recognized and cured at the earlier stage. This work reviews the latest techniques in digital image processing and pattern classification employed for the detection of diabetic retinopathy and compares them on the basis of different performance measures like sensitivity, specificity, accuracy and area under the curve in receiver operating characteristic. The classification of diabetic retinopathy follows various steps like pre-processing, feature extraction and classification of microaneurysm, hemorrhages, exudates and cotton woolen spot. In this paper, the reported literature in each domain is analyzed.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130010184","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: 32
CWT-based detection of roadside vegetation aided by motion estimation 运动估计辅助下基于cwt的路边植被检测
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018405
Iva Harbas, M. Subašić
{"title":"CWT-based detection of roadside vegetation aided by motion estimation","authors":"Iva Harbas, M. Subašić","doi":"10.1109/EUVIP.2014.7018405","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018405","url":null,"abstract":"In this paper we present a method for roadside vegetation detection intended for traffic safety and road infrastructure maintenance. While many published methods are using Near Infrared images which are suitable for vegetation detection, our method uses features from the visible spectrum allowing the use of a common color camera. The presented method uses a set of carefully selected color and texture features. Texture features are based on two-dimensional Continuous Wavelet Transform with oriented wavelets. Because texture can vary as the distance from the camera varies, we limit detection to the regions closer to the camera. We use optical flow as an approximate estimator of distance. The classification is done using nonlinear SVM. For training and testing purposes we recorded our own video database which contains roadside vegetation in various conditions. We present promising experimental results as well as a comparison with several alternative approaches.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125723675","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
New color image illumination enhancement technique based on homomorphic filtering 基于同态滤波的彩色图像照明增强新技术
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018406
Marwa Jmal, W. Souidène, Rabah Attia
{"title":"New color image illumination enhancement technique based on homomorphic filtering","authors":"Marwa Jmal, W. Souidène, Rabah Attia","doi":"10.1109/EUVIP.2014.7018406","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018406","url":null,"abstract":"In this paper, a new color image enhancement technique is proposed. First, input color images are converted to the HSV color space. Then, a new proposed enhancement homomorphic filtering technique is applied on the value component to improve illumination. Finally, a color restoration function is used to overcome the problems of color violation. For the purpose of evaluation, experiments are carried out on the Caltech dataset. The performance of the proposed method is assessed in terms of an image quality measure and compared to the state-of-the-art approaches. It is demonstrated that our approach shows the best results. It succeeded to enhance illumination of images with no loss of details.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134165479","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
An algorithm for automatic people detection from depth map sequences 基于深度图序列的人的自动检测算法
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018368
Denis Brazey, C. Gout
{"title":"An algorithm for automatic people detection from depth map sequences","authors":"Denis Brazey, C. Gout","doi":"10.1109/EUVIP.2014.7018368","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018368","url":null,"abstract":"People detection is a crucial component in many applications such as stadium or building evacuation and marketing analysis. It gives important information on the current number of people in a building or a room. In this work, we propose an algorithm for a real-time people detection system from a sequence of depth images acquired with a vertical depth sensor. The processing pipeline includes a pre-processing and a people segmentation module. The proposed algorithm handles specific situations such as missing or truncated heads. The efficency of the method is evaluated on a set of depth image sequences.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"61 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132155309","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
Real-time enhancement of RGB-D point clouds using piecewise plane fitting 基于分段平面拟合的RGB-D点云实时增强
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018365
Kazuki Matsumoto, François de Sorbier, H. Saito
{"title":"Real-time enhancement of RGB-D point clouds using piecewise plane fitting","authors":"Kazuki Matsumoto, François de Sorbier, H. Saito","doi":"10.1109/EUVIP.2014.7018365","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018365","url":null,"abstract":"In this paper, we propose an efficient framework for reducing noise and holes in depth map captured with an RGB-D camera. This is performed by applying plane fitting to the groups of points assimilable to planar structures and filtering the curved surface points. We present a new method for finding global planar structures in a 3D scene by combining superpixel segmentation and graph component labeling. The superpixel segmentation is based on not only color information but also depth and normal maps. The labeling process is carried out by considering each normal in given superpixel's clusters. We evaluate the reliability of each plane structure and apply the plane fitting only to true planar surfaces. As a result, our system can reduce the noise of the depth map especially on planar area while preserving curved surfaces. The process is done in real-time thanks to GPGPU acceleration via CUDA architecture.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132178616","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
New FMO type to flag ROI in H.264/AVC 在H.264/AVC中标记ROI的新FMO类型
2014 5th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2014-12-01 DOI: 10.1109/EUVIP.2014.7018403
Yongsheng Wang, Máire O’Neill, F. Kurugollu
{"title":"New FMO type to flag ROI in H.264/AVC","authors":"Yongsheng Wang, Máire O’Neill, F. Kurugollu","doi":"10.1109/EUVIP.2014.7018403","DOIUrl":"https://doi.org/10.1109/EUVIP.2014.7018403","url":null,"abstract":"This paper presents a new type of Flexible Macroblock Ordering (FMO) type for the H.264 Advanced Video Coding (AVC) standard, which can more efficiently flag the position and shape of regions of interest (ROIs) in each frame. In H.264/AVC, 7 types of FMO have been defined, all of which are designed for error resilience. Most previous work related to ROI processing has adopted Type-2 (foreground & background), or Type-6 (explicit), to flag the position and shape of the ROI. However, only rectangular shapes are allowed in Type-2 and for non-rectangular shapes, the non-ROI macroblocks may be wrongly flagged as being within the ROI, which could seriously affect subsequent processing of the ROI. In Type-6, each macroblock in a frame uses fixed-length bits to indicate to its slice group. In general, each ROI is assigned to one slice group identity. Although this FMO type can more accurately flag the position and shape of the ROI, it incurs a significant bitrate overhead. The proposed new FMO type uses the smallest rectangle that covers the ROI to indicate its position and a spiral binary mask is employed within the rectangle to indicate the shape of the ROI. This technique can accurately flag the ROI and provide significantly savings in the bitrate overhead. Compared with Type-6, an 80% to 90% reduction in the bitrate overhead can be obtained while achieving the same accuracy.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116199357","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
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