Smart Surveillance Framework

Smart Surveillance Framework

The Smart Surveillance Framework is a C/C++ library built using the OpenCV and the C++ Standard Template Library to provide a set of functionalities to aid researchers not only on the development of surveillance systems but also on the creation of novel solutions for problems related to video surveillance.

One of its main goals is to provide a set of data structures to describe the scene to allow researches to focus only on their problems of interest  and use these information without creating such infrastructure to every problem that will be tackled, as it is done in the majority of case nowadays. For instance, if a researcher is working on individual action recognition, he/she would need the first capture the data, detect and track people, and only then recognize their actions. By using the SSF, one just need to launch detection and tracking modules to provide the people’s location and can concentrate only on the problem at hand, action recognition without worrying about how the data representation, storage and communication has to be designed.


The SSF was designed to provide features for a good scene understanding, scalability, real-time operation, multi-sensor environment, usage of low cost standard components, runtime re-configuration, and communication control.

The main benefits provided by the use of the SSF are the following:

    • A framework to allow the processing of large amounts of data provided by multiple surveillance cameras;
    • A platform to compare and exchange research results in which researchers can contribute with modules to solve specific problems;
    • A framework to allow fast development of new video analysis techniques once one can focus only on his/her specific task;
    • Creation of a high level semantic representation of the scene using data extracted by low level modules to allow activity recognition;
    • A testbed to allow further development on activity understanding since one can focus directly on that using real data, instead of annotated data that may prevent the method from working on real environments.



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Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. If you download the SSF, you automatically agree with it.

NonCommercial — You may not use the SSF for commercial purposes.

Please, cite the following references if you use this framework in your work:

1.Jr., Antonio C. Nazare; Schwartz, William Robson (2016): A scalable and flexible framework for smart video surveillance. In: Computer Vision and Image Understanding, 144 (C), pp. 258–275, 2016. (Type: Article | Links | BibTeX)
2.Jr, A C Nazare; Jr, C E Santos; Ferreira, Renato; Schwartz, W R (2014): Smart Surveillance Framework: A Versatile Tool for Video Analysis. In: IEEE Winter Conference on Applications of Computer Vision, pp. 753–760, 2014. (Type: Inproceeding | Links | BibTeX)


How to create a module in Smart Surveillance Framework

This tutorial aims to demonstrate how to create and configure a new module in SSF.

This requires downloading, besides the framework, the following Visual Studio Project Template. After downloading it, the user must copy it to the folder [UserDocuments]\Visual Studio 2012\Templates\ProjectTemplates.