Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors
Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2014-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/14/9/17112 |
| _version_ | 1818033784701845504 |
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| author | Irfan Mehmood Muhammad Sajjad Sung Wook Baik |
| author_facet | Irfan Mehmood Muhammad Sajjad Sung Wook Baik |
| author_sort | Irfan Mehmood |
| collection | DOAJ |
| description | Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data. |
| first_indexed | 2024-12-10T06:28:46Z |
| format | Article |
| id | doaj.art-0628335f5b864a69bda45742b74904b6 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-12-10T06:28:46Z |
| publishDate | 2014-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0628335f5b864a69bda45742b74904b62022-12-22T01:59:09ZengMDPI AGSensors1424-82202014-09-01149171121714510.3390/s140917112s140917112Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule SensorsIrfan Mehmood0Muhammad Sajjad1Sung Wook Baik2College of Electronics and Information Engineering, Sejong University, Seoul 143-747, KoreaCollege of Electronics and Information Engineering, Sejong University, Seoul 143-747, KoreaCollege of Electronics and Information Engineering, Sejong University, Seoul 143-747, KoreaWireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.http://www.mdpi.com/1424-8220/14/9/17112wireless capsule sensorvideo summarizationmobile-cloud computingenergy savingremote monitoringimplantable sensors |
| spellingShingle | Irfan Mehmood Muhammad Sajjad Sung Wook Baik Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors Sensors wireless capsule sensor video summarization mobile-cloud computing energy saving remote monitoring implantable sensors |
| title | Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors |
| title_full | Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors |
| title_fullStr | Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors |
| title_full_unstemmed | Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors |
| title_short | Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors |
| title_sort | mobile cloud assisted video summarization framework for efficient management of remote sensing data generated by wireless capsule sensors |
| topic | wireless capsule sensor video summarization mobile-cloud computing energy saving remote monitoring implantable sensors |
| url | http://www.mdpi.com/1424-8220/14/9/17112 |
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