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Search for People in Recordings from Security Cameras
Jezerský, Matouš ; Hradiš, Michal (referee) ; Smrž, Pavel (advisor)
This thesis deals with the design and implementation of a system, which allows to search for and recognize people in video recordings. The presented design is based on a preceding research in theory relating to the topics of face and people recognition. Furthermore, the system design is implemented using convolutional neural networks for face recognition, while the implementation primarily utilizes the libraries dlib and OpenFace. The design and implementation use parallelization and distribution of tasks among multiple devices to reduce computation time, while also bearing in mind the practical applications of such system, such as working with limited amounts of available information regarding the person we seek. The precision of people detection and recognition of the implemented system is about 70% to 80%, based on the performed task. Among other uses, the system can be utilized to find a particular person in a video recording, to estimate the number of passes through the monitored space of one person, or the number of passes in total, or to find unknown people in the monitored space.
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Search for People in Recordings from Security Cameras
Jezerský, Matouš ; Hradiš, Michal (referee) ; Smrž, Pavel (advisor)
This thesis deals with the design and implementation of a system, which allows to search for and recognize people in video recordings. The presented design is based on a preceding research in theory relating to the topics of face and people recognition. Furthermore, the system design is implemented using convolutional neural networks for face recognition, while the implementation primarily utilizes the libraries dlib and OpenFace. The design and implementation use parallelization and distribution of tasks among multiple devices to reduce computation time, while also bearing in mind the practical applications of such system, such as working with limited amounts of available information regarding the person we seek. The precision of people detection and recognition of the implemented system is about 70% to 80%, based on the performed task. Among other uses, the system can be utilized to find a particular person in a video recording, to estimate the number of passes through the monitored space of one person, or the number of passes in total, or to find unknown people in the monitored space.
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