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Soft biometrics are biometric traits that do not offer exact human identification, however, they can provide adequate information to narrow-down the search space and give valuable insights for the subject in question. In this work, we examine the issues that emerge by analysing CCTV videos for soft biometrics and propose a methodology for extracting soft biometrics from low-quality and low-resolution video footage taken from real, street CCTV cameras. The proposed approach is based on the concept of Exemplars, that is, to find matches of the examined subject over a labelled dataset, which is able to encode the quality, colour and light variations of the surveillance images. Experiments have been conducted in a new challenging dataset that we introduce in this paper. It has been created using real CCTV footage, enhanced with a wide range of annotations from multiple people, and a manually created segmentation mask for each detection/person. This dataset is made available to scientific community for comparison and improvement of their methodologies in real-world scenarios

Soft biometrics in low resolution and low quality CCTV videos