Specker, AndreasAndreasSpecker2022-03-142022-03-142020https://publica.fraunhofer.de/handle/publica/409179The application of video surveillance systems in public areas to ensure public security is becoming increasingly important. A major task when evaluating the arising amount of video data is to find the occurrences of a person-of-interest on the basis of a testimony. For the comparison of a person's description with persons in the video data, the attributes of all persons must be recognized automatically. However, typical approaches to pedestrian attribute recognition simply predict all attributes for a person, regardless the visibility of relevant attributes. To address this problem, the concept of realistic predictors is used in this work to determine and improve the reliability of pedestrian attribute recognition.en004670conference paper