CONF Anjos_Bob_ACMMM12/IDIAP Bob: a free signal processing and machine learning toolbox for researchers Anjos, André El Shafey, Laurent Wallace, Roy Günther, Manuel McCool, Chris Marcel, Sébastien EXTERNAL https://publications.idiap.ch/attachments/papers/2012/Anjos_Bob_ACMMM12.pdf PUBLIC https://publications.idiap.ch/index.php/publications/showcite/Anjos_Idiap-RR-25-2012 Related documents Proceedings of the ACM Multimedia Conference 2012 https://www.idiap.ch/software/bob/ URL Bob is a free signal processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, Switzerland. The toolbox is designed to meet the needs of researchers by reducing development time and efficiently processing data. Firstly, Bob provides a researcher-friendly Python environment for rapid development. Secondly, efficient processing of large amounts of multimedia data is provided by fast C++ implementations of identified bottlenecks. The Python environment is integrated seamlessly with the C++ library, which ensures the library is easy to use and extensible. Thirdly, Bob supports reproducible research through its integrated experimental protocols for several databases. Finally, a strong emphasis is placed on code clarity, documentation, and thorough unit testing. Bob is thus an attractive resource for researchers due to this unique combination of ease of use, efficiency, extensibility and transparency. Bob is an open-source library and an ongoing community effort. REPORT Anjos_Idiap-RR-25-2012/IDIAP Bob: a free signal processing and machine learning toolbox for researchers Anjos, André El Shafey, Laurent Wallace, Roy Günther, Manuel McCool, Chris Marcel, Sébastien Biometrics computer vision machine learning Open Source pattern recognition signal processing EXTERNAL https://publications.idiap.ch/attachments/reports/2012/Anjos_Idiap-RR-25-2012.pdf PUBLIC Idiap-RR-25-2012 2012 Idiap July 2012 Submitted to the ACM MM 2012 Open Source Software Competition Bob is a free signal processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, Switzerland. The toolbox is designed to meet the needs of researchers by reducing development time and efficiently processing data. Firstly, Bob provides a researcher-friendly Python environment for rapid development. Secondly, efficient processing of large amounts of multimedia data is provided by fast C++ implementations of identified bottlenecks. The Python environment is integrated seamlessly with the C++ library, which ensures the library is easy to use and extensible. Thirdly, Bob supports reproducible research through its integrated experimental protocols for several databases. Finally, a strong emphasis is placed on code clarity, documentation, and thorough unit testing. Bob is thus an attractive resource for researchers due to this unique combination of ease of use, efficiency, extensibility and transparency. Bob is an open-source library and an ongoing community effort.