Title :
A soft-biometrics dataset for person tracking and re-identification
Author :
Schumann, Andrew ; Monari, Eduardo
Author_Institution :
Fraunhofer Inst. for Optronics, Syst. Technol. & Image Exploitation, Germany
Abstract :
In this work we present a new dataset for the tasks person detection, tracking, re-identification, and soft-biometric attribute detection in surveillance data. The dataset was recorded over three days and consists of more than 30 individuals moving through a network of seven cameras. Person tracks are labeled with consistent IDs as well as soft-biometric attributes, such as a description of the clothing, gender, or height. Persons in the video data alter their appearance by changing clothes or wearing accessories. A second, clothing specific ID of each track allows for the evaluation of re-identification with or without the presence of clothing changes. In addition to video and camera calibration data, we provide evaluation protocols, tools and baseline results for each of the four tasks.
Keywords :
biometrics (access control); object tracking; video databases; video signal processing; video surveillance; camera calibration data; clothing specific ID; evaluation protocols; person re-identification; person tracking; soft-biometric attribute detection; soft-biometrics dataset; surveillance data; video calibration data; video data; Accuracy; Cameras; Clothing; Detectors; Histograms; Image color analysis; Surveillance;
Conference_Titel :
Advanced Video and Signal Based Surveillance (AVSS), 2014 11th IEEE International Conference on
Conference_Location :
Seoul
DOI :
10.1109/AVSS.2014.6918667