TrADe Re-ID -- Live Person Re-Identification using Tracking and Anomaly Detection

• URL: http://arxiv.org/abs/2209.06452v1
• Date: Wed, 14 Sep 2022 07:00:35 GMT
• Title: TrADe Re-ID -- Live Person Re-Identification using Tracking and Anomaly Detection
• Authors: Luigy Machaca, F. Oliver Sumari H, Jose Huaman, Esteban Clua, Joris Guerin
• Abstract summary: Person Re-Identification (Re-ID) aims to search for a person of interest in a network of cameras. In the classic Re-ID setting the query is sought in a gallery containing properly cropped images of entire bodies. Recently, the live Re-ID setting was introduced to represent the practical application context of Re-ID better. It consists in searching for the query in short videos, containing whole scene frames.
• Score: 0.6719751155411076
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Person Re-Identification (Re-ID) aims to search for a person of interest (query) in a network of cameras. In the classic Re-ID setting the query is sought in a gallery containing properly cropped images of entire bodies. Recently, the live Re-ID setting was introduced to represent the practical application context of Re-ID better. It consists in searching for the query in short videos, containing whole scene frames. The initial live Re-ID baseline used a pedestrian detector to build a large search gallery and a classic Re-ID model to find the query in the gallery. However, the galleries generated were too large and contained low-quality images, which decreased the live Re-ID performance. Here, we present a new live Re-ID approach called TrADe, to generate lower high-quality galleries. TrADe first uses a Tracking algorithm to identify sequences of images of the same individual in the gallery. Following, an Anomaly Detection model is used to select a single good representative of each tracklet. TrADe is validated on the live Re-ID version of the PRID-2011 dataset and shows significant improvements over the baseline.

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