6533b835fe1ef96bd129f5bb
RESEARCH PRODUCT
Efficient and accurate monitoring of the depth information in a Wireless Multimedia Sensor Network based surveillance
Anthony TannouryChristophe GuyeuxAbdallah MakhoulRony Darazisubject
FOS: Computer and information sciencesComputer scienceComputer Vision and Pattern Recognition (cs.CV)Real-time computingComputer Science - Computer Vision and Pattern Recognition[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technologyImage (mathematics)[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0202 electrical engineering electronic engineering information engineeringWirelessWireless multimedia sensor networksEvent (computing)business.industryNode (networking)Bandwidth (signal processing)020206 networking & telecommunicationsObject (computer science)[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationStereopsis[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]020201 artificial intelligence & image processing[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessdescription
International audience; Abstract—Wireless Multimedia Sensor Network (WMSN) is a promising technology capturing rich multimedia data like audio and video, which can be useful to monitor an environment under surveillance. However, many scenarios in real time monitoring requires 3D depth information. In this research work, we propose to use the disparity map that is computed from two or multiple images, in order to monitor the depth information in an object or event under surveillance using WMSN. Our system is based on distributed wireless sensors allowing us to notably reduce the computational time needed for 3D depth reconstruction, thus permitting the success of real time solutions. Each pair of sensors will capture images for a targeted place/object and will operate a Stereo Matching in order to create a Disparity Map. Disparity maps will give us the ability to decrease traffic on the bandwidth, because they are of low size. This will increase WMSN lifetime. Any event can be detected after computing the depth value for the target object in the scene, and also 3D scene reconstruction can be achieved with a disparity map and some reference(s) image(s) taken by the node(s).
year | journal | country | edition | language |
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2017-09-12 | 2017 Sensors Networks Smart and Emerging Technologies (SENSET) |