Abstract: The present document is directed to automated and semi-automated surveillance and monitoring methods and systems that continuously record digital video, identify and characterize face tracks in the recorded digital video, store the face tracks in a face-track database, and provide query processing functionalities that allow particular face tracks to be quickly identified and used for a variety of surveillance and monitoring purposes. The currently disclosed methods and systems provide, for example, automated anomaly and threat detection, alarm generation, rapid identification of images of parameter-specified individuals within recorded digital video and mapping the parameter-specified individuals in time and space within monitored geographical areas or volumes, functionalities for facilitating human-witness identification of images of individuals within monitored geographical areas or volumes, and many additional functionalities.

Abstract: The present document is directed to automated and semi-automated surveillance and monitoring methods and systems that continuously record digital video, identify and characterize face tracks in the recorded digital video, store the face tracks in a face-track database, and provide query processing functionalities that allow particular face tracks to be quickly identified and used for a variety of surveillance and monitoring purposes. The currently disclosed methods and systems provide, for example, automated anomaly and threat detection, alarm generation, rapid identification of images of parameter-specified individuals within recorded digital video and mapping the parameter-specified individuals in time and space within monitored geographical areas or volumes, functionalities for facilitating human-witness identification of images of individuals within monitored geographical areas or volumes, and many additional functionalities.

Abstract: The present document is directed to methods and systems that identify and characterize face tracks in one or more videos that include frames that contain images of one or more human faces. In certain implementations, values for attributes, such as age, ethnicity, and gender, are assigned to face-containing subimages identified in frames of the image. The occurrence or presence of a face in a sequence of frames is identified, by comparing attributes and location and dimension parameters assigned to each occurrence of the face in a face-containing subimage within a frame, as a face track that represents a four-dimensional tube or cylinder in space time. Attributes are assigned to each face track based on attributes assigned to the occurrences of subimages of the face in frames within the face track.

Abstract: The present document is directed to methods and systems that identify and characterize face tracks in one or more videos that include frames that contain images of one or more human faces. In certain implementations, values for attributes, such as age, ethnicity, and gender, are assigned to face-containing subimages identified in frames of the image. The occurrence or presence of a face in a sequence of frames is identified, by comparing attributes and location and dimension parameters assigned to each occurrence of the face in a face-containing subimage within a frame, as a face track that represents a four-dimensional tube or cylinder in space time. Attributes are assigned to each face track based on attributes assigned to the occurrences of subimages of the face in frames within the face track.