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2017 International Conference on Control, Automation and Information Sciences (ICCAIS)最新文献

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Linear matrix inequalities for dissipative constraints in stabilization with relaxed non-monotonic Lyapunov function 松弛非单调Lyapunov函数镇定中耗散约束的线性矩阵不等式
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217594
T. Tran
{"title":"Linear matrix inequalities for dissipative constraints in stabilization with relaxed non-monotonic Lyapunov function","authors":"T. Tran","doi":"10.1109/ICCAIS.2017.8217594","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217594","url":null,"abstract":"The state feedback design with a relaxed non-monotonic Lyapunov function in the discrete-time domain is developed in this work. Linear matrix inequalities are derived from both dissipation-based constraint and dissipation inequality for the closed-loop system. The dissipation-based constraint facilitates the stabilization with ΔVk  0 and decreasing (not necessarily monotoincally), instead of ΔVk < 0 along the trajectory. Time-invariant matrix inequalities are derived for linear time-invariant systems. State-dependent matrix inequalities are employed in the derivation for nonlinear input-affine systems.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128803292","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
Efficient generalized labeled multi-bernoulli filter for jump Markov system 跃变马尔可夫系统的高效广义标记多伯努利滤波
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217580
Yuthika Punchihewa
{"title":"Efficient generalized labeled multi-bernoulli filter for jump Markov system","authors":"Yuthika Punchihewa","doi":"10.1109/ICCAIS.2017.8217580","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217580","url":null,"abstract":"This paper proposes efficient implementations for a Generalized Labeled Multi-Bernoulli filter for a Jump Markov System. The proposed filter operates via combining both prediction and update steps into a single step, therefore requiring merely a single truncation procedure. The efficiency of the filter is evaluated using simulation examples with comparison to the existing filter with separate prediction and update steps.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114303050","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
A generalized labeled multi-Bernoulli tracker for time lapse cell migration 一种广义标记多伯努利时间移细胞跟踪器
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217576
D. Kim, B. Vo, Aurelne Thian, Yu Suk Choi
{"title":"A generalized labeled multi-Bernoulli tracker for time lapse cell migration","authors":"D. Kim, B. Vo, Aurelne Thian, Yu Suk Choi","doi":"10.1109/ICCAIS.2017.8217576","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217576","url":null,"abstract":"Tracking is a means to accomplish the more fundamental task of extracting relevant information about cell behavior from time-lapse microscopy data. Hence, characterizing uncertainty or confidence in the information inferred from the data is as important as the tracking of the cells. In this paper, we show that in addition to being a principled Bayesian multi-object tracking approach, the Random Finite Set (RFS) framework is capable of providing consistent characterization of uncertainty for the information inferred from the data. In particular, we use an efficient implementation of the Generalized Labeled Multi-Bernoulli (GLMB) filter to track a large number of cells in a cell migration experiment and demonstrate how to characterize uncertainty on variables inferred from the data such as cell counts, survival rate, birth rate, mean position, mean velocity using standard constructs from RFS theory.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134317710","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: 10
EMDs with amplitude information for distributed fusion 具有振幅信息的emd用于分布式融合
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217560
Feng Yang, P. Zhang
{"title":"EMDs with amplitude information for distributed fusion","authors":"Feng Yang, P. Zhang","doi":"10.1109/ICCAIS.2017.8217560","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217560","url":null,"abstract":"Exponential Mixture Densities (EMDs) is increasingly popular as a suboptimal distributed fusion technique that avoids calculating the common information between different nodes. However, there exists some concerns about the EMDs because it fuses the cluttered posterior density as a whole, which contains plenty of components of little physical significance. Thus, it becomes intractable and computation expensive especially when targets are closely spaced or heavy clutters are distributed in the vicinity of targets. To address this problem, in this paper, a EMDs-based fusion algorithm with amplitude information is proposed. Considering the amplitude of target returns is stronger than that coming from false alarm, and the amplitude from each target is distinctly different, here, the amplitude information is utilized to identify targets and clutters. We implement this approach using Gaussian Mixture techniques and demonstrate the effectiveness and high estimation accuracy of the proposed algorithm over the EMDs algorithm and traditional Covariance Intersection (CI) algorithm.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131229901","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
Deep neural network for person re-identification in a non-overlapping camera network 基于深度神经网络的非重叠摄像机网络人再识别
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217574
Hyunguk Choi, M. Jeon
{"title":"Deep neural network for person re-identification in a non-overlapping camera network","authors":"Hyunguk Choi, M. Jeon","doi":"10.1109/ICCAIS.2017.8217574","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217574","url":null,"abstract":"Person re-identification is important and challenging parts in a non-overlapping camera network. In this paper, we propose the person re-identification framework which consists of kernel size into convolutional layers considering the person ratio and relationship matrix that train the relationship information related to neighborhoods. Our framework deals with global feature extracted from the whole body. The features generated by suitable kernel size are different to the local featured making by separated body images. The approaches of local feature extracted from divided bodies tend to lose salient information because of cutting the characteristic of products. The extracted features are used as elements to learn a relationship matrix which plays a role in distinction function. Our proposed framework outperforms state-of-the-art methods on challenging datasets.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133092863","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
Multiple extended target tracking based on GLMB filter and gibbs sampler 基于GLMB滤波器和gibbs采样器的多扩展目标跟踪
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217587
Yimei Chen, Weifeng Liu, Xudong Wang
{"title":"Multiple extended target tracking based on GLMB filter and gibbs sampler","authors":"Yimei Chen, Weifeng Liu, Xudong Wang","doi":"10.1109/ICCAIS.2017.8217587","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217587","url":null,"abstract":"In this paper, a new multiple extended target tracking learning algorithm based on labelled random finite sets (L-RFS) framework is proposed to estimate the number, shape and state of extended targets under clutter conditions. The algorithm mainly includes two aspects: multi-extended target dynamic modeling and multi-extended target tracking estimates. Firstly, a finite mixture model (FMM) of extended target is established under the generalized labelled multi-bernoulli (GLMB) filter. Learning the parameters of finite mixture model by Gibbs sampling and Bayesian information criterion (BIC), and then equivalent point target measurements are used in place of the actual extended target measurements. Finally, the proposed ellipse approximation model is used to realize the estimation of the extended target shape. The simulation results show that the proposed algorithm can effectively track the multiple extended targets and obtain the shape of extended target.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127898212","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
Object retrieval in past video using bag-of-words model 基于词袋模型的过去视频对象检索
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217565
Manh-Tien Nguyen-Hoang, Tu-Khiem Le, Van-Tu Ninh, Quoc-Huu Che, Vinh-Tiep Nguyen, M. Tran
{"title":"Object retrieval in past video using bag-of-words model","authors":"Manh-Tien Nguyen-Hoang, Tu-Khiem Le, Van-Tu Ninh, Quoc-Huu Che, Vinh-Tiep Nguyen, M. Tran","doi":"10.1109/ICCAIS.2017.8217565","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217565","url":null,"abstract":"Together with the technology advancement, Computer Vision plays an important role in enhancing smart computing systems to help people overcome obstacles in their daily lives. One of the common troublesome problems is human memorization ability, especially memorizing things such as personal items. It is annoying for people to waste their time finding lost items manually by recall or notes. This motivates the authors to propose a solution that can help a user find an item that he or she already saw but vaguely remembers where and when it appeared in the past. The user simply provides our system a single image of that item, then the system retrieves a rank list of visual scenes that may contain the item from video recorded implicitly during user's daily activities. Our method is based on Bag-of-Words model, one of the most famous methods in image retrieval. We first conduct experiments to find the appropriate parameters and configurations of Bag-of-Words system for visual instance search. Then we perform experiments with 110 visual queries of 30 common objects in real video with 2837 shots recorded during daily activities of volunteers. Experimental results show that for all 30/30 categories of objects, our system can help users find their objects of interest just by looking into the top 10 video shots retrieved from recorded video with the balance accuracy from 50 to 80%. This demonstrates the potential use of our method to help people remind of their items in an easy and comfortable way.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129392081","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
Multi-sensor tracking with non-overlapping field for the GLMB filter GLMB滤波器的无重叠多传感器跟踪
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217575
Weifeng Liu, Yimei Chen, Hailong Cui, Quanbo Ge
{"title":"Multi-sensor tracking with non-overlapping field for the GLMB filter","authors":"Weifeng Liu, Yimei Chen, Hailong Cui, Quanbo Ge","doi":"10.1109/ICCAIS.2017.8217575","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217575","url":null,"abstract":"In this paper, we consider multi-sensor with non-overlapping radar field of view in the framework of labeled random finite sets (L-RFS). In this case, a target may be simultaneously observed by some of the sensors, or even none sensor. It is different from the existing assumption of all sensors with the same fields in tracking community. We first describe the field of view by modeling the detection of probability of individual sensors. Then, a multi-sensor measurement-driven of birth model is proposed. We solve this problem by using the generalized labeled multi-Bernoulli (GLMB) filter. In the final simulation, a three-target & three-sensor is given to verify the effectiveness of the proposed algorithm.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130008260","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
Complex wavelet transform-based approach for human action recognition in video 基于复小波变换的视频人体动作识别方法
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217568
M. Khare, Jeonghwan Gwak, M. Jeon
{"title":"Complex wavelet transform-based approach for human action recognition in video","authors":"M. Khare, Jeonghwan Gwak, M. Jeon","doi":"10.1109/ICCAIS.2017.8217568","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217568","url":null,"abstract":"Human action recognition is a challenging research in computer vision applications because variety of human actions can be misclassified as some other action types. In this paper, we proposed a method for human action recognition based on dual tree complex wavelet transform (DTCWT). DTCWT has better edge representation and approximate shift-invariant properties compared to real-valued wavelet transforms. Experiments are carried out on different standard action datasets including KTH and MSR. We have performed the proposed method on multiple levels of DTCWT. The proposed method is compared with other state-of-the-art methods in terms of different quantitative performance measures, and the results of the proposed method are found to have better recognition accuracy.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126052976","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
Occlusion detector using convolutional neural network for person re-identification 用卷积神经网络遮挡检测器进行人的再识别
2017 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2017-10-01 DOI: 10.1109/ICCAIS.2017.8217564
Sejeong Lee, Yoojin Hong, M. Jeon
{"title":"Occlusion detector using convolutional neural network for person re-identification","authors":"Sejeong Lee, Yoojin Hong, M. Jeon","doi":"10.1109/ICCAIS.2017.8217564","DOIUrl":"https://doi.org/10.1109/ICCAIS.2017.8217564","url":null,"abstract":"Technique of comparing pedestrian images observed by different cameras to determine whether they are the same person is important in the surveillance system. This technique is called Person re-identification. Most of Person reidentification is underway assuming that occlusion does not occur. However, since occlusion occurs frequently in the surveillance system and affects accuracy, it is necessary to determine whether the occlusion occurs before applying person re-identification in the real environment. In order to deal with occlusion, we introduce occlusion detector based convolutional neural networks that determine occlusion of an input image. We also created an occlusion dataset through data augmentation and learned the occlusion detector using this dataset. We have achieved 98.7% accuracy of the data obtained by synthesizing occlusion in public dataset.","PeriodicalId":410094,"journal":{"name":"2017 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115900676","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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