2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)最新文献

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White-box traceable dynamic attribute based encryption 基于白盒可跟踪动态属性的加密
Zechao Liu, Xuan Wang, Lei Cui, Z. L. Jiang, Chunkai Zhang
{"title":"White-box traceable dynamic attribute based encryption","authors":"Zechao Liu, Xuan Wang, Lei Cui, Z. L. Jiang, Chunkai Zhang","doi":"10.1109/SPAC.2017.8304334","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304334","url":null,"abstract":"Ciphertext policy attribute-based encryption (CP-ABE) is a promising technology that offers fine-grained access control over encrypted data. In a CP-ABE scheme, any user can decrypt the ciphertext using his secret key if his attributes satisfy the access policy embedded in the ciphertext. Since the same ciphertext can be decrypted by multiple users with their own keys, the malicious users may intentionally leak their decryption keys for financial profits. So how to trace the malicious users becomes an important issue in a CP-ABE scheme. In addition, from the practical point of view, users may leave the system due to resignation or dismissal. So user revocation is another hot issue that should be solved. In this paper, we propose a practical CP-ABE scheme. On the one hand, our scheme has the properties of traceability and large universe. On the other hand, our scheme can solve the dynamic issue of user revocation. The proposed scheme is proved selectively secure in the standard model.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"37 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125683190","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
Multi-view based coupled dictionary learning for person re-identification 基于多视图的人再识别耦合字典学习
Fei Ma, Qinglong Liu, Xiaoke Zhu, Xiaoyuan Jing
{"title":"Multi-view based coupled dictionary learning for person re-identification","authors":"Fei Ma, Qinglong Liu, Xiaoke Zhu, Xiaoyuan Jing","doi":"10.1109/SPAC.2017.8304357","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304357","url":null,"abstract":"Person re-identification is a hot topic, which can be applied in pedestrian tracking and intelligent monitoring. However, person reidentification is challenging due to the large variations of visual appearance caused by view angle, lighting, background clutter and occlusion. In practice, there exist large differences among different types of features and among different cameras. To improve the favorable representation of different features, we propose a multi-view based coupled dictionary pair learning approach, which can learn the color features and texture features respectively. The color dictionary pair aims to learn the color feature of each person from different cameras. The texture dictionary pair seeks to learn the texture feature of person from both cameras. The learned coupled dictionary pair can demonstrate the intrinsic relationship of different cameras and different types of features. Experimental results on two public pedestrian datasets demonstrate that our proposed approach can perform better than the other competing methods.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132778111","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
Attribute weighted Naive Bayes for remote sensing image classification based on cuckoo search algorithm 基于布谷鸟搜索算法的属性加权朴素贝叶斯遥感图像分类
Juan Yang, Z. Ye, Xu Zhang, W. Liu, Huazhong Jin
{"title":"Attribute weighted Naive Bayes for remote sensing image classification based on cuckoo search algorithm","authors":"Juan Yang, Z. Ye, Xu Zhang, W. Liu, Huazhong Jin","doi":"10.1109/SPAC.2017.8304270","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304270","url":null,"abstract":"The Naive Bayes classifier(NB) is an effective and simple classification method for remote sensing image classification which is based on probability theory. However, in general, the contribution of each feature is different for classification and its attribute independence assumption is often invalid in the real world. The attribute weighted Naive Bayes(WNB) classifier might have better performance compared to NB, nevertheless, it is a hard and time-consuming work to learn the weight values for all features. Cuckoo search is a newly proposed meta-heuristic optimization algorithm which has been successfully applied for many parameter optimization problems. In the paper, a remote image classification approach is proposed, the attribute weight of which is learnt through cuckoo search algorithm (CSWNB in brief). In order to testify the performance of the proposed method, it is compared to some other evolutionary algorithms, such as attributed weighted Naive Bayes based on Genetic Algorithm (GAWNB), attributed weighted Naive Bayes based on Particle Swarm Optimization (PSOWNB) and attributed weighted Naive Bayes based on Water Wave Optimization (WWOWNB) etc. Experimental results demonstrate that the proposed approach has higher classification accuracy and more stable performance.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126863013","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: 14
Learning to focus for object proposals 学习关注目标提议
Zijing Chen, Xinhua You, Jun Li
{"title":"Learning to focus for object proposals","authors":"Zijing Chen, Xinhua You, Jun Li","doi":"10.1109/SPAC.2017.8304319","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304319","url":null,"abstract":"Object proposal generators address the wasteful exhaustive search of the sliding window scheme in visual object detection and have been shown effective. However, the number of candidate windows is still large in order to ensure full coverage of potential objects. This paper presents a complementary technique that aims to work with any proposal generating system, amending the workflow from “propose-assess” to “propose-adjust-assess”. The adjustment serves as an auto-focus mechanism for the system and reduces the number of object proposals to be processed. The auto-focus is realized by two learning-based transformation models, one translating and the other deforming the windows towards better alignments of the objects, which are trained for identifying generic objects using image cues. Experiments on reallife image data sets show that the proposed technique can reduce the number of proposals without loss of performance.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126600653","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
Face liveness detection with recaptured feature extraction 基于特征提取的人脸活动性检测
Xiao Luan, Huaming Wang, Weihua Ou, Linghui Liu
{"title":"Face liveness detection with recaptured feature extraction","authors":"Xiao Luan, Huaming Wang, Weihua Ou, Linghui Liu","doi":"10.1109/SPAC.2017.8304317","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304317","url":null,"abstract":"Face recognition systems can be tricked by photos or videos with virtual faces. It is crucial for a safe face recognition system to distinguish genuine user's faces (i.e., the first captured images of real scene) and spoof faces (i.e., recaptured images of photographs or videos). Existing face liveness methods often use single image feature to address face spoofing problems, which are not reliable and robust. In this paper, we analyze the differences between genuine face images and spoof images, and propose to extract three types of features, i.e., specular reflection ratio, Hue channel distribution and blurriness, to determine whether a face image is captured from genuine face or not. Experimental results on NUAA photograph imposter database show the competitive performance of our method comparing with several state-of-the-art methods.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121189242","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: 17
Vehicle detection and tracking based on optical field 基于光场的车辆检测与跟踪
Zhenyu Guo, Ziqi Zhou, Xiaoting Sun
{"title":"Vehicle detection and tracking based on optical field","authors":"Zhenyu Guo, Ziqi Zhou, Xiaoting Sun","doi":"10.1109/SPAC.2017.8304352","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304352","url":null,"abstract":"Vehicle detection and tracking are of great significance on computer vision and practical applications. The main task of it is to pick out vehicles from the images in a realtime video and tag them so as to achieve goals like traffic flow calculation and the driving direction estimate. In this essay, we chose Horn-Schunck method based on optical field to detect the vehicles. Without knowing any background information, this method can precisely process the video in a real time, picking out the statistics of the moving car and count them. The algorithm used in the essay can achieve the goal of vehicle detection and tracking, calculating and show vehicle flow precisely and avoid the interference of pedestrians and other irrelevant factors.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"3 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113960040","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
Color-luminance adjustment for image cloning based on mean-value coordinates 基于均值坐标的图像克隆彩色亮度调整
Zhongqian Jiang, Xun Gong, Hao Fei
{"title":"Color-luminance adjustment for image cloning based on mean-value coordinates","authors":"Zhongqian Jiang, Xun Gong, Hao Fei","doi":"10.1109/SPAC.2017.8304287","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304287","url":null,"abstract":"Image cloning could seamlessly copy and paste the interesting region from the source image into the target image to produce natural-looking and pleasing cloned result. This paper proposes an efficient color-luminance adjustment method to preserve the color of source image in object cloned region while insure the seamless transition between the source image and target image. We use an improved mean-value coordinates cloning to generate a mean-value membrane, and modulate the membrane according to automatic computed weighted parameter in different color channels. Furthermore, a constrained weighted parameter is utilized to make the cloned result match well with the target image on the luminance. The experimental results demonstrate that our method could obtain natural-looking and pleasing cloned result.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121690610","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
An improved active contour model driven by region-scalable and local Gaussian-distribution fitting energy 一种基于区域可伸缩和局部高斯分布拟合能量驱动的改进活动轮廓模型
Wei Zhang, Bin Fang, X. Wu, Jiye Qian, Weibin Yang, Shenhai Zheng
{"title":"An improved active contour model driven by region-scalable and local Gaussian-distribution fitting energy","authors":"Wei Zhang, Bin Fang, X. Wu, Jiye Qian, Weibin Yang, Shenhai Zheng","doi":"10.1109/SPAC.2017.8304315","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304315","url":null,"abstract":"Images with low contrast, overlapped noise and intensity inhomogeneity of multiple objects make many existing level set methods disabled for image segmentation. To address the problem, an improved active contour model is proposed, driving by region-scalable and local Gaussian-distribution fitting energy for image segmentation. Firstly, we classify regions with similar intensity by utilizing the means and variances of local image intensities. Secondly, we define a new edge stopping functional to robustly capture the boundaries of multiple objects. Finally, we utilize LoG energy term to catch edge information and smooth the homogeneous regions, which can be optimized by an energy function. Experiments results on real and synthetic images validate that our method is faster, robuster and higher accuracy than other major region-based methods for images with multiple objects.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133328974","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
Imitation and memory-based self-organizing behaviors under voluntary vaccination 自愿接种下基于模仿和记忆的自组织行为
Guangliang Liu, Hongjun Qiu, B. Shi, Zhen Wang
{"title":"Imitation and memory-based self-organizing behaviors under voluntary vaccination","authors":"Guangliang Liu, Hongjun Qiu, B. Shi, Zhen Wang","doi":"10.1109/SPAC.2017.8304328","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304328","url":null,"abstract":"Understanding human voluntary vaccinating behaviors plays essential roles in designing incentive-based vaccination programs for public health authorities to eliminate or eradicate an vaccine-preventable disease. Usually, individuals make vaccinating decisions by weighing the cost of vaccination and infection, which can be perceived based on their vaccinating experiences. However, in reality, an individual's decision can also be influenced by others. Along this line, in this paper, we present an imitation and memory-based self-organization mechanism to investigate human voluntary vaccinating behaviors, which takes into consideration both individuals' historical experiences and the impact of social influence. Through carrying out simulations on flu-like seasonal diseases, we evaluate the combined effects of both imitation and memory on the final vaccine coverage level with respect to different relative cost of vaccination and infection. Simulation results show that the imitation-based behavior has a greater impact on public vaccine coverage level than the memory-based rational behavior under voluntary vaccination, which emphasizes the importance of social guidance in disease intervention and control.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134303395","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
Faster R-CNN based microscopic cell detection 更快的基于R-CNN的显微细胞检测
Su Yang, Bin Fang, Wei Tang, X. Wu, Jiye Qian, Weibin Yang
{"title":"Faster R-CNN based microscopic cell detection","authors":"Su Yang, Bin Fang, Wei Tang, X. Wu, Jiye Qian, Weibin Yang","doi":"10.1109/SPAC.2017.8304302","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304302","url":null,"abstract":"The automatic analysis of microscopic images is an important subject of medical image processing, of which the cell detection is an important part. However, owing to the different size and shape, as also as the adhesion among cells, detecting and locating cells accurately seems to be a very challenging task. In this work, we investigate applying the Faster R-CNN, which has recently shown incredible performance on many public datasets, to cell detection. The Faster R-CNN contains both segmentation and classification. By training a Faster R-CNN model, a series of experiments are achieved. Experimental results show that the Faster R-CNN can detect almost all cells in a microscopic image. The proposed cell detector has improved detection performance, and it is easy-implemented and time-saving.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124947943","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: 23
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