Project Details

Description

This projects deals with vision-based person re-identification to measure queue times in, e.g., an airport. The primary goal of this project is to develop very discriminative features to distinguish persons that have been captured by non-overlapping cameras. Having cameras located at the queue entrance and exit, features from the corresponding views can be matched to find the time from a person entered the queue to leaving.
StatusFinished
Effective start/end date01/01/201731/12/2019

Keywords

  • person re-identification
  • multimodal
  • convolution neural network
  • feature fusion