Pub Date : 2015-06-01DOI: 10.1109/ICME.2015.7177433
Jinzhuo Wang, Wenmin Wang, Ronggang Wang, Wen Gao
Spatial pyramid (SP) representation is an extension of bag-of-feature model which embeds spatial layout information of local features by pooling feature codes over pre-defined spatial shapes. However, the uniform style of spatial pooling shapes used in standard SP is an ad-hoc manner without theoretical motivation, thus lacking the generalization power to adapt to different distribution of geometric properties across image classes. In this paper, we propose a data-driven approach to adaptively learn class-specific pooling shapes (CSPS). Specifically, we first establish an over-complete set of spatial shapes providing candidates with more flexible geometric patterns. Then the optimal subset for each class is selected by training a linear classifier with structured sparsity constraint and color distribution cues. To further enhance the robust of our model, the representations over CSPS are compressed according to the shape importance and finally fed to SVM with a multi-shape matching kernel for classification task. Experimental results on three challenging datasets (Caltech-256, Scene-15 and Indoor-67) demonstrate the effectiveness of the proposed method on both object and scene images.
{"title":"Learning class-specific pooling shapes for image classification","authors":"Jinzhuo Wang, Wenmin Wang, Ronggang Wang, Wen Gao","doi":"10.1109/ICME.2015.7177433","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177433","url":null,"abstract":"Spatial pyramid (SP) representation is an extension of bag-of-feature model which embeds spatial layout information of local features by pooling feature codes over pre-defined spatial shapes. However, the uniform style of spatial pooling shapes used in standard SP is an ad-hoc manner without theoretical motivation, thus lacking the generalization power to adapt to different distribution of geometric properties across image classes. In this paper, we propose a data-driven approach to adaptively learn class-specific pooling shapes (CSPS). Specifically, we first establish an over-complete set of spatial shapes providing candidates with more flexible geometric patterns. Then the optimal subset for each class is selected by training a linear classifier with structured sparsity constraint and color distribution cues. To further enhance the robust of our model, the representations over CSPS are compressed according to the shape importance and finally fed to SVM with a multi-shape matching kernel for classification task. Experimental results on three challenging datasets (Caltech-256, Scene-15 and Indoor-67) demonstrate the effectiveness of the proposed method on both object and scene images.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122227918","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}
Pub Date : 2015-06-01DOI: 10.1109/ICME.2015.7177425
E. Sokic, S. Konjicija
Contour-based Fourier descriptors are established as a simple and effective shape description method for content-based image retrieval. In order to achieve invariance under rotation and starting point change, most Fourier descriptor implementations disregard the phase of the Fourier coefficients. We introduce a novel method for extracting Fourier descriptors, which preserve the phase of Fourier coefficients and have the desired invariance. We propose specific points, called pseudomirror points, to be used as shape orientation reference. Experimental results indicate that the proposed method significantly outperforms other Fourier descriptor based techniques.
{"title":"Shape description using phase-preserving Fourier descriptor","authors":"E. Sokic, S. Konjicija","doi":"10.1109/ICME.2015.7177425","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177425","url":null,"abstract":"Contour-based Fourier descriptors are established as a simple and effective shape description method for content-based image retrieval. In order to achieve invariance under rotation and starting point change, most Fourier descriptor implementations disregard the phase of the Fourier coefficients. We introduce a novel method for extracting Fourier descriptors, which preserve the phase of Fourier coefficients and have the desired invariance. We propose specific points, called pseudomirror points, to be used as shape orientation reference. Experimental results indicate that the proposed method significantly outperforms other Fourier descriptor based techniques.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"637 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115114015","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}
Pub Date : 2015-06-01DOI: 10.1109/ICME.2015.7177475
Lida Li, Lin Zhang, Hongyu Li
In this paper, we propose a novel 3D ear classification scheme, making use of the label consistent K-SVD (LC-KSVD) framework. As an effective supervised dictionary learning algorithm, LC-KSVD learns a compact discriminative dictionary for sparse coding and a multi-class linear classifier simultaneously. To use LC-KSVD, one key issue is how to extract feature vectors from 3D ear scans. To this end, we propose a block-wise statistics based scheme. Specifically, we divide a 3D ear ROI into blocks and extract a histogram of surface types from each block; histograms from all blocks are concatenated to form the desired feature vector. Feature vectors extracted in this way are highly discriminative and are robust to mere misalignment. Experimental results demonstrate that the proposed approach can achieve much better recognition accuracy than the other state-of-the-art methods. More importantly, its computational complexity is extremely low at the classification stage.
{"title":"3D ear identification using LC-KSVD and local histograms of surface types","authors":"Lida Li, Lin Zhang, Hongyu Li","doi":"10.1109/ICME.2015.7177475","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177475","url":null,"abstract":"In this paper, we propose a novel 3D ear classification scheme, making use of the label consistent K-SVD (LC-KSVD) framework. As an effective supervised dictionary learning algorithm, LC-KSVD learns a compact discriminative dictionary for sparse coding and a multi-class linear classifier simultaneously. To use LC-KSVD, one key issue is how to extract feature vectors from 3D ear scans. To this end, we propose a block-wise statistics based scheme. Specifically, we divide a 3D ear ROI into blocks and extract a histogram of surface types from each block; histograms from all blocks are concatenated to form the desired feature vector. Feature vectors extracted in this way are highly discriminative and are robust to mere misalignment. Experimental results demonstrate that the proposed approach can achieve much better recognition accuracy than the other state-of-the-art methods. More importantly, its computational complexity is extremely low at the classification stage.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130730202","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}
Pub Date : 2015-06-01DOI: 10.1109/ICME.2015.7177380
Simone Zennaro, Matteo Munaro, S. Milani, P. Zanuttigh, A. Bernardi, S. Ghidoni, E. Menegatti
Microsoft Kinect had a key role in the development of consumer depth sensors being the device that brought depth acquisition to the mass market. Despite the success of this sensor, with the introduction of the second generation, Microsoft has completely changed the technology behind the sensor from structured light to Time-Of-Flight. This paper presents a comparison of the data provided by the first and second generation Kinect in order to explain the achievements that have been obtained with the switch of technology. After an accurate analysis of the accuracy of the two sensors under different conditions, two sample applications, i.e., 3D reconstruction and people tracking, are presented and used to compare the performance of the two sensors.
{"title":"Performance evaluation of the 1st and 2nd generation Kinect for multimedia applications","authors":"Simone Zennaro, Matteo Munaro, S. Milani, P. Zanuttigh, A. Bernardi, S. Ghidoni, E. Menegatti","doi":"10.1109/ICME.2015.7177380","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177380","url":null,"abstract":"Microsoft Kinect had a key role in the development of consumer depth sensors being the device that brought depth acquisition to the mass market. Despite the success of this sensor, with the introduction of the second generation, Microsoft has completely changed the technology behind the sensor from structured light to Time-Of-Flight. This paper presents a comparison of the data provided by the first and second generation Kinect in order to explain the achievements that have been obtained with the switch of technology. After an accurate analysis of the accuracy of the two sensors under different conditions, two sample applications, i.e., 3D reconstruction and people tracking, are presented and used to compare the performance of the two sensors.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133731346","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}
Pub Date : 2015-06-01DOI: 10.1109/ICME.2015.7177407
Haoyu Ren, Ze-Nian Li
Object tracking is one of the most important components in numerous applications of computer vision. In this paper, the target is represented by a series of binary patterns, where each binary pattern consists of several rectangle pairs in variable size and location. As complementary to traditional binary descriptors, these patterns are extracted in both the intensity domain and the gradient domain. In the tracking process, the RealAdaBoost algorithm is adopted frame by frame to select the meaningful patterns while considering the discriminative ability and the robustness. This is achieved by a penalty term based on the classification margin and structural diversity. As a result, the features good at describing the target and robust to noises will be selected. Experimental results on 10 challenging video sequences demonstrate that the tracking accuracy is significantly improved compared to traditional binary descriptors. It also achieves competitive results with the commonly-used algorithms.
{"title":"Object tracking using structure-aware binary features","authors":"Haoyu Ren, Ze-Nian Li","doi":"10.1109/ICME.2015.7177407","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177407","url":null,"abstract":"Object tracking is one of the most important components in numerous applications of computer vision. In this paper, the target is represented by a series of binary patterns, where each binary pattern consists of several rectangle pairs in variable size and location. As complementary to traditional binary descriptors, these patterns are extracted in both the intensity domain and the gradient domain. In the tracking process, the RealAdaBoost algorithm is adopted frame by frame to select the meaningful patterns while considering the discriminative ability and the robustness. This is achieved by a penalty term based on the classification margin and structural diversity. As a result, the features good at describing the target and robust to noises will be selected. Experimental results on 10 challenging video sequences demonstrate that the tracking accuracy is significantly improved compared to traditional binary descriptors. It also achieves competitive results with the commonly-used algorithms.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"66 14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133444244","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}
Pub Date : 2015-06-01DOI: 10.1109/ICME.2015.7177484
D. N. Tran, Hyukzae Lee, Changick Kim
Heart rate (HR) is an important indicator of human health status. Traditional heart rate measurement methods rely on contact-based sensors or electrodes, which are inconvenient and troublesome for users. Remote sensing of the photoplephysmography (PPG) signal using a video camera provides a promising means to monitor vital signs of people without the need of any physical contact. However, until recently, most of the literature papers approaching this problem have only reported results from off-line recording videos taken under well controlled environments. In this paper, we propose a method to improve HR measurement accuracy under challenging environments involving factors such as subjects movement, complicated facial models (i.e., hair, glass, beards, etc.), subjects' distance to camera, and low illumination condition. We also build a framework for real-time measuring system and construct a stable model for recording and displaying results for long term heart rate monitoring. We tested our system on challenging dataset, and demonstrated that our method not only deals with real-time, on-line measurement tasks, but also outperforms others' works.
{"title":"A robust real time system for remote heart rate measurement via camera","authors":"D. N. Tran, Hyukzae Lee, Changick Kim","doi":"10.1109/ICME.2015.7177484","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177484","url":null,"abstract":"Heart rate (HR) is an important indicator of human health status. Traditional heart rate measurement methods rely on contact-based sensors or electrodes, which are inconvenient and troublesome for users. Remote sensing of the photoplephysmography (PPG) signal using a video camera provides a promising means to monitor vital signs of people without the need of any physical contact. However, until recently, most of the literature papers approaching this problem have only reported results from off-line recording videos taken under well controlled environments. In this paper, we propose a method to improve HR measurement accuracy under challenging environments involving factors such as subjects movement, complicated facial models (i.e., hair, glass, beards, etc.), subjects' distance to camera, and low illumination condition. We also build a framework for real-time measuring system and construct a stable model for recording and displaying results for long term heart rate monitoring. We tested our system on challenging dataset, and demonstrated that our method not only deals with real-time, on-line measurement tasks, but also outperforms others' works.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"23 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133291896","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}
Pub Date : 2015-06-01DOI: 10.1109/ICME.2015.7177398
Yu-Lin Wang, A. Su, Tseng-Ying Han, Ching-Lun Lin, Ling-Chi Hsu
For the patients suffering from amyotrophic lateral sclerosis (ALS), they are encouraged to exercise their bodies routinely to prevent or delay the paralysis of muscles. This work proposes an electromyogram (EMG) based ALS rehabilitation system via playing computer games. The multi-channel EMG measuring system and the controlled interfaces to computer games were developed. According to the symptoms of disability, the controls from different muscles are designed. For ALS patients in the early stage, the EMG electrodes were placed on the forearm to detect the finger gestures; for ALS patients in the middle stage, the EMG signals of upper extremity were employed to detect the hand gestures and arm moving; for the late ALS stage, the EMG electrodes were placed on chin to detect the facial expression. A commercial video game as well as a self-modified computer game are utilized in our rehabilitation systems. We believe that the patients are more preferable to exercise their bodies in a form of entertainment.
{"title":"EMG based rehabilitation systems - approaches for ALS patients in different stages","authors":"Yu-Lin Wang, A. Su, Tseng-Ying Han, Ching-Lun Lin, Ling-Chi Hsu","doi":"10.1109/ICME.2015.7177398","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177398","url":null,"abstract":"For the patients suffering from amyotrophic lateral sclerosis (ALS), they are encouraged to exercise their bodies routinely to prevent or delay the paralysis of muscles. This work proposes an electromyogram (EMG) based ALS rehabilitation system via playing computer games. The multi-channel EMG measuring system and the controlled interfaces to computer games were developed. According to the symptoms of disability, the controls from different muscles are designed. For ALS patients in the early stage, the EMG electrodes were placed on the forearm to detect the finger gestures; for ALS patients in the middle stage, the EMG signals of upper extremity were employed to detect the hand gestures and arm moving; for the late ALS stage, the EMG electrodes were placed on chin to detect the facial expression. A commercial video game as well as a self-modified computer game are utilized in our rehabilitation systems. We believe that the patients are more preferable to exercise their bodies in a form of entertainment.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127831787","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}
Different features describe different views of visual appearance, multi-view based methods can integrate the information contained in each view and improve the image clustering performance. Most of the existing methods assume that the importance of one type of feature is the same to all the data. However, the visual appearance of images are different, so the description abilities of different features vary with different images. To solve this problem, we propose a group-aware multi-view fusion approach. Images are partitioned into groups which consist of several images sharing similar visual appearance. We assign different weights to evaluate the pairwise similarity between different groups. Then the clustering results and the fusion weights are learned by an iterative optimization procedure. Experimental results indicate that our approach achieves promising clustering performance compared with the existing methods.
{"title":"GOMES: A group-aware multi-view fusion approach towards real-world image clustering","authors":"Zhe Xue, Guorong Li, Shuhui Wang, Chunjie Zhang, W. Zhang, Qingming Huang","doi":"10.1109/ICME.2015.7177392","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177392","url":null,"abstract":"Different features describe different views of visual appearance, multi-view based methods can integrate the information contained in each view and improve the image clustering performance. Most of the existing methods assume that the importance of one type of feature is the same to all the data. However, the visual appearance of images are different, so the description abilities of different features vary with different images. To solve this problem, we propose a group-aware multi-view fusion approach. Images are partitioned into groups which consist of several images sharing similar visual appearance. We assign different weights to evaluate the pairwise similarity between different groups. Then the clustering results and the fusion weights are learned by an iterative optimization procedure. Experimental results indicate that our approach achieves promising clustering performance compared with the existing methods.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129963614","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}
Pub Date : 2015-06-01DOI: 10.1109/ICME.2015.7177430
Cuiling Lan, Jizheng Xu, Wenjun Zeng, Feng Wu
We present a compound image compression scheme based on the dictionary-based Lempel-Ziv-Markov chain algorithm (LZMA), under the framework of High Efficiency Video Coding (HEVC). Through matching strings from the sliding window dictionary, LZMA exploits the characteristics of the repeated patterns over the text and graphics regions of compound images, and represents them compactly. To obtain high compression efficiency even for noisy text and graphics contents, we have modified LZMA to support both lossless and lossy compression. We develop and treat it as a new intramode of HEVC. Experimental results show that the proposed scheme achieves significant coding gains for compound image compression. Thanks to the introduction of the lossy LZMA, the compression performance for noisy compound images is improved for more than 5dB in terms of PSNR in comparison with the lossless LZMA scheme.
{"title":"Compound image compression using lossless and lossy LZMA in HEVC","authors":"Cuiling Lan, Jizheng Xu, Wenjun Zeng, Feng Wu","doi":"10.1109/ICME.2015.7177430","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177430","url":null,"abstract":"We present a compound image compression scheme based on the dictionary-based Lempel-Ziv-Markov chain algorithm (LZMA), under the framework of High Efficiency Video Coding (HEVC). Through matching strings from the sliding window dictionary, LZMA exploits the characteristics of the repeated patterns over the text and graphics regions of compound images, and represents them compactly. To obtain high compression efficiency even for noisy text and graphics contents, we have modified LZMA to support both lossless and lossy compression. We develop and treat it as a new intramode of HEVC. Experimental results show that the proposed scheme achieves significant coding gains for compound image compression. Thanks to the introduction of the lossy LZMA, the compression performance for noisy compound images is improved for more than 5dB in terms of PSNR in comparison with the lossless LZMA scheme.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115695835","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}
Pub Date : 2015-06-01DOI: 10.1109/ICME.2015.7177431
Fei Cheng, Jimin Xiao, T. Tillo
In this paper, a motion-information-based 3D video coding method is proposed for the texture plus depth 3D video format. The synchronized global motion information of camcorder is sampled to assist the encoder to improve its rate-distortion performance. This approach works by projecting temporal previous frames into the position of the current frame using the depth and motion information. These projected frames are added in the reference buffer as virtual reference frames. As these virtual reference frames are more similar to the current frame than the conventional reference frames, the required residual information is reduced. The experimental results demonstrate that the proposed scheme enhances the coding performance in various motion conditions including rotational and translational motions.
{"title":"3D video coding using motion information and depth map","authors":"Fei Cheng, Jimin Xiao, T. Tillo","doi":"10.1109/ICME.2015.7177431","DOIUrl":"https://doi.org/10.1109/ICME.2015.7177431","url":null,"abstract":"In this paper, a motion-information-based 3D video coding method is proposed for the texture plus depth 3D video format. The synchronized global motion information of camcorder is sampled to assist the encoder to improve its rate-distortion performance. This approach works by projecting temporal previous frames into the position of the current frame using the depth and motion information. These projected frames are added in the reference buffer as virtual reference frames. As these virtual reference frames are more similar to the current frame than the conventional reference frames, the required residual information is reduced. The experimental results demonstrate that the proposed scheme enhances the coding performance in various motion conditions including rotational and translational motions.","PeriodicalId":146271,"journal":{"name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","volume":"42 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131273621","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}
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