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2017 2nd International Conference on Image, Vision and Computing (ICIVC)最新文献

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A cost effective method for automobile security based on detection and recognition of human face 一种基于人脸检测与识别的低成本汽车安全方法
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984557
Kanza Gulzar, Jun Sang, Omar Tariq
{"title":"A cost effective method for automobile security based on detection and recognition of human face","authors":"Kanza Gulzar, Jun Sang, Omar Tariq","doi":"10.1109/ICIVC.2017.7984557","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984557","url":null,"abstract":"The proposed system for automobile security is a face detection and recognition application that control the automobile to be operated or restricted. This system is established for all types of door locks and particularly for automobiles. By using this methodology, resulted a better quality product with respect to documentation standards, code optimization, user acceptance due to adequately efficient, maintainable, consistence and cheaper software. With the up-to-date and influential technology, the system is not only expected to be workable, but also sufficiently efficient in terms of execution speed and response time. In our work we studied the limitations of the face recognition techniques and try to give the best solution with benefits of both fisherface and eigenface recognition methods at minimum cost. As the main aim of this work is to develop a low cost security system for a common man to keep his automobile save but it does not only protects the automobile but also assist in catching the thief by saving his image. This paper defines an efficient face detection and recognition algorithms using a cross platform of EmguCV as .Net wrapper to the Intel OpenCV library, Visual Studio and C# .Net, with hardware components essentially a Computer Stick and an Arduino uno.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132972042","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
Hybrid organization and visualization of the DSM combined with 3D building model 结合三维建筑模型的DSM混合组织与可视化
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984619
Linlu Gan, Jun Yu Li, N. Jing
{"title":"Hybrid organization and visualization of the DSM combined with 3D building model","authors":"Linlu Gan, Jun Yu Li, N. Jing","doi":"10.1109/ICIVC.2017.7984619","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984619","url":null,"abstract":"Aiming at the geometric deformation of city buildings at the most sophisticated LOD of digital surface model(DSM) derived from oblique photogrammetry automatic modeling, we have proposed a method of organizing and visualizing the DSM combined with fine building model on the virtual globe based on WebGL and 3D Tiles. This method has resolved the problems of correlated organization of the DSM with manual model, and unified scheduling and rendering of the hybrid models. We have visualized the hybrid models by some data processing works, including flattening the mesh which presented building model and pruning redundant triangular patches at most precise tiles of LOD in the DSM, computing inserting node and associating metadata information of the fine building model with the spatial data structure of the DSM. This method can effectively solve the multi-level organization and scheduling of the hybrid models and enhance the visualization effect.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126705567","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
The analysis of topic's personality traits using a new topic model 用一个新的话题模型分析话题的人格特征
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984720
Zheng Hu, Yishan Liu, Chunhong Zhang, Yingnan Xu
{"title":"The analysis of topic's personality traits using a new topic model","authors":"Zheng Hu, Yishan Liu, Chunhong Zhang, Yingnan Xu","doi":"10.1109/ICIVC.2017.7984720","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984720","url":null,"abstract":"Topic model is a powerful technique for topic discovery from text. In this paper, we establish connections between topic and personality that offers rationality of topic's personality traits. We build a new generation model which can directly get the relationship between topic and personality. The model has been validated on real data set of users in Sina Weibo. Our experiments give the quantitative result of topic's personality traits and present interpretability for the relationship between topic and personality.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126064494","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
Tensor-based weighted least square decomposition haze removal algorithm 基于张量的加权最小二乘分解雾霾去除算法
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984723
Xin Jin, Xiaotong Wang, Xiaogang Xu, Chengtao Yi, Changqing Yang
{"title":"Tensor-based weighted least square decomposition haze removal algorithm","authors":"Xin Jin, Xiaotong Wang, Xiaogang Xu, Chengtao Yi, Changqing Yang","doi":"10.1109/ICIVC.2017.7984723","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984723","url":null,"abstract":"Haze removal is a challenging work in outdoor image applications. Physical model based restoration methods are accepted with higher pertinence, while non-physical model based enhancement methods are more robust and widely applied. A novel haze removal algorithm based on tensor weighted least square decomposition was presented in this paper. By either progressively or recursively applying this decomposition, a set of multiscale outputs and differences were obtained. Then haze images were got dehazed by suppressing the haze layer while enhancing the extracted detail layers. The effectiveness and robustness of our haze removal algorithm were demonstrated by comparing our results with existing generally acknowledged dark channel prior based method.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121151286","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
The research of 3D parametric modeling method along railways based on cylindrical projection 基于圆柱投影的铁路沿线三维参数化建模方法研究
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984616
Li Zheng, Liang Yongshu, Liu Kunming
{"title":"The research of 3D parametric modeling method along railways based on cylindrical projection","authors":"Li Zheng, Liang Yongshu, Liu Kunming","doi":"10.1109/ICIVC.2017.7984616","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984616","url":null,"abstract":"This study proposes a method of parametric modeling by using DOM and LiDAR point cloud date, aiming to respectively analyses the features of ground object model and obtain partial feature point coordinates of ground object. Besides, a specific method of triangle network connection is adopted to build a 3D ground object model and finally maps the model to display. The method has following advantages: efficiency and fast; high degree of automation met the requirements of exhibition of the railway 3D GIS. Meanwhile, based on the model built by point cloud date, huge workload of placing ground object model can be reduced during the latter period of inputting 3D terrain.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116208460","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
Urban expansion monitoring in South Asia based on SPOT /VGT and DMSP/OLS data 基于SPOT /VGT和DMSP/OLS数据的南亚城市扩张监测
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984732
Zhaohua Liu, Jinhua Huang, Rui Wang, C. Zhou, Linlin Lu
{"title":"Urban expansion monitoring in South Asia based on SPOT /VGT and DMSP/OLS data","authors":"Zhaohua Liu, Jinhua Huang, Rui Wang, C. Zhou, Linlin Lu","doi":"10.1109/ICIVC.2017.7984732","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984732","url":null,"abstract":"Based on time series data of SPOT / VGT and DMSP / OLS, the built-up and non-built-up areas of countries in South Asia were extracted via the local support vector machine method. Accuracy assessment showed that Kappa coefficients were above 0.85 were achieved in 1998 and 2013. Based on built-up areas detected, the urban expansion of the eight South Asian countries and their major cities were analyzed from 1998 to 2013. Combining with the country's population and GDP data, the development of the eight countries during the study period were discussed.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"271 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115253201","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
Introducing an in-core hybrid LU implementation on heterogeneous systems 在异构系统上引入核心内混合逻辑单元实现
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984721
Cheng Chen, Canqun Yang
{"title":"Introducing an in-core hybrid LU implementation on heterogeneous systems","authors":"Cheng Chen, Canqun Yang","doi":"10.1109/ICIVC.2017.7984721","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984721","url":null,"abstract":"Matrix factorization (MF) is a employed by many algorithms, such as collaborating filtering, text mining and deriving hidden features of words. Out-of-core heterogeneous MF implementations are recently used to take advantage of state-of-the-art architecture and can solve problems larger than the available memory of coprocessors. Due to the data set cannot fit into the limited amount of device memory, frequently data transfers take place between the hosts and coprocessors via the costly PCIe bus. With the increasing of coprocessor's in-card memory, we introduce an in-core hybrid MF algorithm, e.g. LU factorization, on a CPU-MIC system to minimize such data movement. Validation on the Tianhe-2 supercomputer shows that our in-core implementation competes with the highly optimized MKL which is an out-of-core hybrid LU implementation and achieves about 5 × speedup versus the CPU version.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"255 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121218764","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
Research of visual tracking based on prior knowledge 基于先验知识的视觉跟踪研究
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984647
Liheng Wang, Longwu Sun
{"title":"Research of visual tracking based on prior knowledge","authors":"Liheng Wang, Longwu Sun","doi":"10.1109/ICIVC.2017.7984647","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984647","url":null,"abstract":"Despite the high maneuverability of Human's finger in videos, there are some principle in this kind of motion. A prior knowledge base is built on historical observation information .To solve the problem that Kalman filter responses not timely enough toward moving fingers in gesture videos, an adaptive acceleration extremum according to prior knowledge in current statistical (CS) model is introduced. On the other hand, taking advantage of interactive multi model (IMM) algorithm, the mixed models are used to make up for the inaccuracy of knowledge base when the motion pattern is unusual. Furthermore, motion termination forecast from prior knowledge base alters the model transition probability, boosting the speed of response in IMM. Simulations and practical engineering proves that the algorithm proposed by this article track efficiently in low quality videos whether the finger's trajectory is straight or tortuous.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123884811","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
Parallelizing band selection for hyperspectral imagery with many-threads 多线程高光谱图像的并行波段选择
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984607
X. Gan, Jie Liu
{"title":"Parallelizing band selection for hyperspectral imagery with many-threads","authors":"X. Gan, Jie Liu","doi":"10.1109/ICIVC.2017.7984607","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984607","url":null,"abstract":"It is time-consuming and expensive for band selection of hyperspectral imagery. In practice, band selection for hyperspectral imagery is a computing-intensive application, in which bands with less information are removed and the maximal information band should be preserved by quantifying information amount based on K-L divergence. Fortunately, it is suitable to parallelize band selection for hyperspectral imagery using accelerator with many-threads. Experimental results validate that band selection with China Accelerator would be much better than CPU and 1.25 X speedups than that of matched GPU.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"224 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133269831","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
Fine-grained object detection based on self-adaptive anchors 基于自适应锚的细粒度目标检测
2017 2nd International Conference on Image, Vision and Computing (ICIVC) Pub Date : 2017-06-01 DOI: 10.1109/ICIVC.2017.7984522
Kaili Ma, Jun Zhang, Fenglei Wang, D. Tu, Shuohao Li
{"title":"Fine-grained object detection based on self-adaptive anchors","authors":"Kaili Ma, Jun Zhang, Fenglei Wang, D. Tu, Shuohao Li","doi":"10.1109/ICIVC.2017.7984522","DOIUrl":"https://doi.org/10.1109/ICIVC.2017.7984522","url":null,"abstract":"The fine-grained object detection is an extremely challenging problem due to the subtle variances in the appearances. At present, faster R-CNN is one of the best detection systems. However, it not a wise decision to directly apply the faster R-CNN to the fine-grained object detection. By analyzing the characteristics of fine-grained objects, we found that the anchor mechanism in the faster R-CNN system has a lot of redundancy. By analyzing the characteristics of fine-grained objects, we use self-adaptive anchors to enhance the structure of the system and combine the detection and classification of fine-grained objects. By using self-adaptive anchors, new progress has been made on the small-scale fine-grained datasets (Stanford Cars).We making the detection of mean average precision on the Stanford Cars dataset flush to 88.9%. And we notice that this mechanism used in non-fine-grained detection does not decrease its effect. So this mechanism, which is named self-adaptable anchors, can be used as a general idea in object detection.","PeriodicalId":181522,"journal":{"name":"2017 2nd International Conference on Image, Vision and Computing (ICIVC)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115606722","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
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