MeshEye: A Hybrid-Resolution Smart Camera Mote for Applications in Distributed Intelligent Surveillance

By Stephan Hengstler, D. Prashanth, Sufen Fong, H. Aghajan. International Symposium on Information Processing in Sensor Networks, 2007

296 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/df3097978489549a30a30701d591e9646e43f18d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Ian F. Akyildiz
2. Tommaso Melodia
3. Wendi Rabiner Heinzelman
4. Stanislava Soro
5. Kaushik R. Chowdhury

In Electrical and Electronic Engineering

1. Ian F. Akyildiz
2. Tommaso Melodia
3. Kaushik R. Chowdhury
4. Stanislava Soro
5. José Maria Barceló-Ordinas
6. Wendi Rabiner Heinzelman
7. Kemal Bicakci
8. Ruken Zilan

In Global and Planetary Change

1. Wendi Rabiner Heinzelman
2. Stanislava Soro

Citations in the corpus

• A Survey of Visual Sensor Networks (2009, methodology): “For example, the Mesheye architecture [ 5 ] uses two low resolution image sensors (kilopixels) and one high resolution (VGA) image sensor located in between the two low resolution image sensors.”
• A survey of visual sensor network platforms (2012, background): “No data compression or coding results are reported for either MeshEye [19] or MicrelEye [23] platforms.”
• Wireless Multimedia Sensor Networks: Applications and Testbeds (2008, methodology): “The MeshEye mote proposed in [ 19 ] addresses this challengebyatwo-tieredapproach.Alow-resolutionstereo vision system is used to gather data that help to determine the position, range, and size of moving objects.”