# Efficient and accurate monitoring of the depth information in a Wireless Multimedia Sensor Network based surveillance

## TL;DR

This paper presents a distributed method for real-time 3D depth monitoring in Wireless Multimedia Sensor Networks using disparity maps, reducing computational load and bandwidth for surveillance applications.

## Contribution

It introduces a distributed stereo matching approach that enables efficient, real-time depth estimation and scene reconstruction in WMSNs, enhancing surveillance capabilities.

## Key findings

- Reduced computational time for 3D depth reconstruction.
- Lower bandwidth usage due to small disparity maps.
- Enabled real-time detection and scene reconstruction.

## 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).