2013 18th International Conference on Digital Signal Processing (DSP)最新文献_第8页

Hand posture recognition using K-NN and Support Vector Machine classifiers evaluated on our proposed HandReader dataset 使用K-NN和支持向量机分类器对我们提出的HandReader数据集进行评估的手部姿势识别

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622679

Ghassem Tofighi, A. Venetsanopoulos, K. Raahemifar, S. Beheshti, Helia Mohammadi

{"title":"Hand posture recognition using K-NN and Support Vector Machine classifiers evaluated on our proposed HandReader dataset","authors":"Ghassem Tofighi, A. Venetsanopoulos, K. Raahemifar, S. Beheshti, Helia Mohammadi","doi":"10.1109/ICDSP.2013.6622679","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622679","url":null,"abstract":"In this paper, we propose a real-time vision-based hand posture recognition approach, based on appearance-based features of the hand poses. Our approach has three main steps: Preprocessing, Feature Extraction and Posture Recognition. Additionally, a new hand posture dataset called HandReader is created and introduced. HandReader is a dataset of 500 images of 10 different hand postures which are 10 non-motion-based American Sign Language alphabets with dark backgrounds. The dataset is gathered by capturing images of 50 male and female individuals performing these 10 hand postures in front of a common camera. 20% of the HandReader images are used for the training purpose and the remaining 80% are used to test the proposed methodology. All the images are normalized after applying the preprocessing step. The normalized images are then converted to feature vectors in the Feature Extraction step. In order to train the system, k-NN classifier and SVM classifiers with linear and RBF kernel have been employed and results were compared. These approaches were used to classify hand posture images into 10 different posture classes. The SVM classifier with linear kernel performed better with the highest true detection rate (96%) among other proposed techniques.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130220535","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: 11

Estimating Tremor in Vocal Fold Biomechanics for Neurological Disease Characterization 估计声带震颤的神经系统疾病表征的生物力学

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622735

P. G. Vilda, Victor Nieto Lluis, M. V. R. Biarge, Agustín Álvarez Marquina, Luis Miguel Mazaira-Fernández, R. Martínez, Cristina Muñoz-Mulas, Mario Fernández-Fernández, Carlos Ramírez-Calvo

引用次数: 11

Tex-Lex: Automated generation of texture lexicons using images from the world wide web Tex-Lex:使用万维网上的图像自动生成纹理词典

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622814

Demetrios Gerogiannis, Christophoros Nikou

{"title":"Tex-Lex: Automated generation of texture lexicons using images from the world wide web","authors":"Demetrios Gerogiannis, Christophoros Nikou","doi":"10.1109/ICDSP.2013.6622814","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622814","url":null,"abstract":"A method for automatic creation of a semantic texture database is introduced, which exploits the cumulative knowledge that exists in the image tags on the World Wide Web. In the first step of the method, a number of images are retrieved from the Web using the text search option provided by search engines by querying simple notions (e.g. sky, grass water, etc.). These images are segmented into a number of predefined regions using standard clustering and each region is described by a set of image features. The descriptors of the extracted regions of the whole set of images are compared based on the Bhattacharyya distance and the ones that are more similar are considered to be entries of a dictionary associated with the initial keyword used for the query. Moreover, the corresponding regions are parts of the visual lexicon describing the keyword. Also, an already existing lexicon may be iteratively updated by new features that may not match the existing dictionary entries but they are represented over a significant number of query results. Early results on common keywords representing landscapes indicate that the method is promising and may be extended to describe composite structures and objects.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133350921","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

Single-image super-resolution using low complexity adaptive iterative back-projection 使用低复杂度自适应迭代反投影的单图像超分辨率

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622833

G. Georgis, G. Lentaris, D. Reisis

引用次数: 8

Gait-based gender recognition using pose information for real time applications 基于步态的性别识别，利用姿势信息进行实时应用

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622766

Dimitris Kastaniotis, Ilias Theodorakopoulos, G. Economou, S. Fotopoulos

{"title":"Gait-based gender recognition using pose information for real time applications","authors":"Dimitris Kastaniotis, Ilias Theodorakopoulos, G. Economou, S. Fotopoulos","doi":"10.1109/ICDSP.2013.6622766","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622766","url":null,"abstract":"Biological cues inherent in human motion play an important role in the context of social communication. While recognizing the gender of other people is important for humans, security, advertisement and population statistics systems could also benefit from such kind of information. In this work for first time we propose a method suitable for real time gait based gender recognition relying on poses estimated from depth images. We provide evidence that pose based representation estimated by depth images could greatly benefit the problem of gait analysis. Given a gait sequence, in every frame the dynamics of gait motion are encoded using an angular representation. In particular several skeletal primitives are expressed as two Euler angles that cast votes into aggregated histograms. These histograms are then normalized, concatenated and projected onto a PCA basis in order to form the final sequence descriptor. We evaluated our method on a newly created dataset -UPCVgait - captured with Microsoft Kinect, consisting of 5 gait sequences performed by 30 subjects. An RBF kernel SVM used for classification in a leave one person out scheme on gait sequences of arbitrary length as well as on variable number of frames confirms the efficiency of our method.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"599 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116451796","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: 41

Neural network target classification for Concealed Weapon radar detection 隐蔽武器雷达探测中的神经网络目标分类

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622819

A. Vasalos, N. Uzunoglu, H. Ryu, I. Vasalos

引用次数: 1

Experiments on far-field multichannel speech processing in smart homes 智能家居中远场多通道语音处理实验

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622707

I. Rodomagoulakis, Panagiotis Giannoulis, Z.-I. Skordilis, P. Maragos, G. Potamianos

引用次数: 7

Active contour model driven by Globally Signed Region Pressure Force 全局签名区域压力驱动的活动等值线模型

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622691

M. Abdelsamea, S. Tsaftaris

{"title":"Active contour model driven by Globally Signed Region Pressure Force","authors":"M. Abdelsamea, S. Tsaftaris","doi":"10.1109/ICDSP.2013.6622691","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622691","url":null,"abstract":"One of the most popular and widely used global active contour models (ACM) is the region-based ACM, which relies on the assumption of homogeneous intensity in the regions of interest. As a result, most often than not, when images violate this assumption the performance of this method is limited. Thus, handling images that contain foreground objects characterized by multiple intensity classes present a challenge. In this paper, we propose a novel active contour model based on a new Signed Pressure Force (SPF) function which we term Globally Signed Region Pressure Force (GSRPF). It is designed to incorporate, in a global fashion, the skewness of the intensity distribution of the region of interest (ROI). It can accurately modulate the signs of the pressure force inside and outside the contour, it can handle images with multiple intensity classes in the foreground, it is robust to additive noise, and offers high efficiency and rapid convergence. The proposed GSRPF is robust to contour initialization and has the ability to stop the curve evolution close to even ill-defined (weak) edges. Our model provides a parameter-free environment to allow minimum user intervention, and offers both local and global segmentation properties. Experimental results on several synthetic and real images demonstrate the high accuracy of the segmentation results in comparison to other methods adopted from the literature.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122052774","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: 21

Spatial sound rendering for dynamic virtual environments 动态虚拟环境的空间声音渲染

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622815

B. Cowan, B. Kapralos

引用次数: 4

Two-stage audio-visual speech dereverberation and separation based on models of the interaural spatial cues and spatial covariance 基于耳间空间线索和空间协方差模型的两阶段视听语音去噪与分离

2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622780

Muhammad Salman Khan, S. M. Naqvi, J. Chambers

{"title":"Two-stage audio-visual speech dereverberation and separation based on models of the interaural spatial cues and spatial covariance","authors":"Muhammad Salman Khan, S. M. Naqvi, J. Chambers","doi":"10.1109/ICDSP.2013.6622780","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622780","url":null,"abstract":"This work presents a two-stage speech source separation algorithm based on combined models of interaural cues and spatial covariance which utilize knowledge of the locations of the sources estimated through video. In the first pre-processing stage the late reverberant speech components are suppressed by a spectral subtraction rule to dereverberate the observed mixture. In the second stage, the binaural spatial parameters, the interaural phase difference and the interaural level difference, and the spatial covariance are modeled in the short-time Fourier transform (STFT) domain to classify individual time-frequency (TF) units to each source. The parameters of these probabilistic models and the TF regions assigned to each source are updated with the expectation-maximization (EM) algorithm. The algorithm generates TF masks that are used to reconstruct the individual speech sources. Objective results, in terms of the signal-to-distortion ratio (SDR) and the perceptual evaluation of speech quality (PESQ), confirm that the proposed multimodal method with pre-processing is a promising approach for source separation in highly reverberant rooms.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"11 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123682649","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: 7