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2016 International Conference on Audio, Language and Image Processing (ICALIP)最新文献

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Forum topic detection based on hierarchical clustering 基于层次聚类的论坛主题检测
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846583
Hui Li, Qing Li
{"title":"Forum topic detection based on hierarchical clustering","authors":"Hui Li, Qing Li","doi":"10.1109/ICALIP.2016.7846583","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846583","url":null,"abstract":"Forum has become one of the main platforms for people to express their personal point of view, with a lot of information surging in the forum everyday. How to detect automatically a forum topic among the massive information becomes an important and hard task. Though there are plenty of studies for topic detection, it is still a challenge to make it fast and accurately. This paper introduces the principle of maximum entropy and information gain when calculating feature weight. Our algorithm is based on the agglomerative hierarchical clustering (AHC). Experiments are focused on a game forum and handling sparse forum short texts. The result shows that the improved method can detect the forum topic more effectively.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129992816","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
The analysis method of video camera's motion based on optical flow and slam 基于光流和冲击的摄像机运动分析方法
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846577
Pan Wang, Chen Chen, Chunyan Dong, Haojun Xu, Feng Tian
{"title":"The analysis method of video camera's motion based on optical flow and slam","authors":"Pan Wang, Chen Chen, Chunyan Dong, Haojun Xu, Feng Tian","doi":"10.1109/ICALIP.2016.7846577","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846577","url":null,"abstract":"This paper presents a method of video shot motion analysis based on LK optical flow method to solve the problem of film video shot motion of visual comfortable effect. A segmentation method based on footage of two class support vector machine classification is used. The optical flow method based on the hierarchical Lucas-Kanade in Pyramid combined with SLAM Algorithm to extract the motion information of the lens is used. Then the motion type of the shot is analyzed. Experimental results show that the method is not only able to achieve a good shot segmentation, but also the segmentation of the shot can be a good analysis of the results. Compared to the traditional optical flow method, the method has a higher accuracy. Finally it can analysis a movie, and get the distribution of different shots in the movie.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121714076","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
Multi-source localization based on approximated kernel density estimator and spatial likelihood function in near-field reverberant environment 近场混响环境下基于近似核密度估计和空间似然函数的多源定位
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846625
Yuzhuo Fang, Xu Zhi-yong, Zhao Zhao
{"title":"Multi-source localization based on approximated kernel density estimator and spatial likelihood function in near-field reverberant environment","authors":"Yuzhuo Fang, Xu Zhi-yong, Zhao Zhao","doi":"10.1109/ICALIP.2016.7846625","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846625","url":null,"abstract":"In order to cope with the multi-source localization in near-field reverberant environment, approximated kernel density estimator (KDE) algorithm is introduced to provide robust anti-reverberation performance and multi-stage (MS) is used to solve the spectrum aliasing of high frequency on account of wide spacing of microphone array. Then spatial likelihood function (SLF) is built to mix the pairwise KDE or KDEMS function together. Based on the above KDE, MS, SLF, two algorithms SLF-KDE, SLF-KDEMS is proposed. The feasibility of the methods is confirmed by theoretical derivation and computer simulation. The results shows that SLF-KDEMS is a localization algorithm with high robustness and recognition in near-field reverberant environment.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128788872","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 of individual object in focus people group based on deep learning 基于深度学习的焦点人群个体目标识别
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846607
Liu Hui-bin, Wu Fei, Chen Qiang, Pan Yong
{"title":"Recognition of individual object in focus people group based on deep learning","authors":"Liu Hui-bin, Wu Fei, Chen Qiang, Pan Yong","doi":"10.1109/ICALIP.2016.7846607","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846607","url":null,"abstract":"Deep leaning has become a hot research topic with the rapid development of big data technology. As an important branch of deep learning, convolutional neural network has been widely used in image recognition, and has achieved great success. Convolutional architecture for fast feature embedding (Caffe) with features like speed, extendibility and openness is currently top popular tool of deep learning. In this paper, the authors use Caffe to realize the recognition of individual object in a focus people group. The training images can be obtained from the video recorded by the camera through the method of normalized cross-correlation histogram. The experimental results show that the individual object can be matched accurately by using pre training model. It can be used in practical work like attendance system, criminal investigation field etc.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127447541","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
WiFi indoor localization based on K-means 基于K-means的WiFi室内定位
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846667
Yazhou Zhong, Fei Wu, Juan Zhang, B. Dong
{"title":"WiFi indoor localization based on K-means","authors":"Yazhou Zhong, Fei Wu, Juan Zhang, B. Dong","doi":"10.1109/ICALIP.2016.7846667","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846667","url":null,"abstract":"A large number of studies show that in complex indoor propagation environment, parameters of indoor positioning method for typical applications, such as localization performance of TOA, TDOA, AOA, RSSI method is often less than ideal. In order to reduce the influence of indoor environmental factors on the indoor wireless positioning, improve the positioning accuracy and expand the location area, the indoor wireless positioning method based on WiFi K-means is proposed. The improved distance formula is used to take into account the effect of attribute values, and the difference between different objects can be calculated more accurately. The AP in the position of each room is established by testing the signal strength of different signals. The experimental results show that the precision in location probability of 3 meters is more than 80%, which relative than hard clustering algorithm, positioning accuracy is improved.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128599930","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: 12
Research of vehicle speed detection algorithm in video surveillance 视频监控中车速检测算法的研究
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846573
Jinxiang Wang
{"title":"Research of vehicle speed detection algorithm in video surveillance","authors":"Jinxiang Wang","doi":"10.1109/ICALIP.2016.7846573","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846573","url":null,"abstract":"The paper presented a vehicle speed estimation algorithm based on moving target detection in video surveillance. Firstly, the features of moving vehicles were extracted by using the three frame difference method and the background difference method; secondly, tracked and positioned the moving target according to moving vehicle centroid feature extraction method; finally, the vehicle speed was estimated based on mapping relationship between the pixel distance with the actual distance.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"2008 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128999644","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: 24
An adaptive fast algorithm based on variance for AVS2 基于方差的AVS2自适应快速算法
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846592
Ling-An Zeng, Fan Liang, Liwei Xie
{"title":"An adaptive fast algorithm based on variance for AVS2","authors":"Ling-An Zeng, Fan Liang, Liwei Xie","doi":"10.1109/ICALIP.2016.7846592","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846592","url":null,"abstract":"In the second generation of Audio Video coding Standard(AVS2), the encoder tries all possible depth levels in order to select the best partition pattern for coding unit (CU) and prediction unit (PU). In this paper, we proposed an adaptive fast algorithm based on variance, which can effectually reduce the total encoding time with negligible bitrate increment for AVS2. Our algorithm utilizes the variance values which can represent the characters of the input image to determine the modes of CU partition and PU partition quickly. Simulation results show that the proposed algorithm can reduce the encoding time by 21%, 31% and 31% on average and only increase the bitrate by 0.58%, 0.17% and 0.16% in all intra, low delay and random access configuration compared to RD 12.0. The top performance of encoding time can be saved up to 69% just with 0.69% bitrate increment. The time reduction of our algorithm is most outstanding on high-definition (HD) video sequences.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122866356","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
Image processing of cement-based materials in conditions of current flow for microstructural analysis 水流条件下水泥基材料显微结构分析的图像处理
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846545
Jiangping Hu, A. Susanto, D. Koleva
{"title":"Image processing of cement-based materials in conditions of current flow for microstructural analysis","authors":"Jiangping Hu, A. Susanto, D. Koleva","doi":"10.1109/ICALIP.2016.7846545","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846545","url":null,"abstract":"This paper reports the results of microstructural analysis based on image analysis subjected to electrical current as a simulation of stray current effect. The purpose is to investigate the influence of electrical current flow on the development of microstructural properties in reinforced cement-based materials. In view of the significant contribution to material performance, the characterization of cement-based microstructure in an economical and reliable way is of high relevance to permeability prediction and durability studies of cement-based materials. In this study, taking the cement paste submerged in Ca(OH)2 conditions as specimens, the pore size distribution and percolation was derived from image analysis of ESEM micrographs. The electrical properties of mortars were measured and their microstructural characteristics were investigated using quantitative image analysis techniques. Moreover this approach is compared with other general methods such as mercury intrusion porosimetry (MIP) and the comparison shows good consistency in development of parameters characterizing the materials' microstructure.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121220172","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
Distance aggregation for person re-identification using simulated annealing algorithm 基于模拟退火算法的人再识别距离聚合
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846659
Kang Han, W. Wan, Guoliang Chen, Li Hou
{"title":"Distance aggregation for person re-identification using simulated annealing algorithm","authors":"Kang Han, W. Wan, Guoliang Chen, Li Hou","doi":"10.1109/ICALIP.2016.7846659","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846659","url":null,"abstract":"The aim of person re-identification is to match pedestrians which across disjoint camera views. Many features have been proposed to improve the re-identification accuracy. However, due to significant person appearance variations in viewpoints, poses, and illumination across different cameras, individual feature is less discriminative to represent the different person images. In this paper, we propose an effective and easy-to-apply distance aggregation method to combine different features. The individual distance are firstly obtained by metric learning. Then we use simulated annealing algorithm to learn different distance weight. Experimental results demonstrate that the proposed method significantly outperforms the existing methods in VIPeR dataset.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128736121","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: 2
Modeling motion flow using tensor dynamic textures 使用张量动态纹理建模运动流
2016 International Conference on Audio, Language and Image Processing (ICALIP) Pub Date : 2016-07-01 DOI: 10.1109/ICALIP.2016.7846642
Bingyin Zhou, Qingyun Ren, Ming Lu
{"title":"Modeling motion flow using tensor dynamic textures","authors":"Bingyin Zhou, Qingyun Ren, Ming Lu","doi":"10.1109/ICALIP.2016.7846642","DOIUrl":"https://doi.org/10.1109/ICALIP.2016.7846642","url":null,"abstract":"As a family of visual patterns in moving scenes with certain temporal regularity, dynamic textures are powerful visual cues for people to understand things; hence, effective models are needed for relevant applications. Considering that image sequences are really tensor time series, this paper proposes a tensor dynamic texture model to represent dynamic texture videos, and a sub-optimal algorithm to estimate the model parameters. Our tensor-based method can capture multiple interactions and essential structures in videos. Experimental results on dynamic texture synthesis show that the proposed method not only achieved a better visual quality, but also a smaller model size and a less time cost. The maximum PSNR gain achieves 2.36 dB, and the maximum model size reduction achieves 49.68%.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115942251","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
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