Efficient and accurate monitoring of the depth information in a Wireless Multimedia Sensor Network based surveillance
This addresses the need for efficient depth information in surveillance scenarios using WMSNs, but it appears incremental as it applies existing stereo matching techniques to this domain.
The paper tackles the problem of real-time 3D depth monitoring in Wireless Multimedia Sensor Networks (WMSNs) by using disparity maps from multiple images, resulting in reduced computational time and bandwidth traffic to enable real-time solutions and increase network lifetime.
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).