Two stream deep CNN-RNN attentive pooling architecture for video-based person re-identification

W. Ansar, M. M. Fraz, M. Shahzad, I. Gohar, S. Javed, S. K. Jung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations


Person re-identification (re-ID), is the task of associating the relationship among the images of a person captured from different cameras with non-overlapping field of view. Fundamental and yet an open issue in re-ID is extraction of powerful features in low resolution surveillance videos. In order to solve this, a novel Two Stream Convolutional Recurrent model with Attentive pooling mechanism is presented for person re-ID in videos. Each stream of the model is a Siamese network which is aimed at extracting and matching most differentiated feature maps. Attentive pooling is used to select most informative video frames. The output of two streams is fused to formulate one combined feature map, which helps to deal with major challenges of re-ID e.g. pose and illumination variation, clutter background and occlusion. The proposed technique is evaluated on three challenging datasets: MARS, PRID-2011 and iLIDS-VID. Experimental evaluation shows that the proposed technique performs better than existing state-of-the-art supervised video based person re-ID models. The implementation is available at

Original languageBritish English
Title of host publicationProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 23rd Iberoamerican Congress, CIARP 2018, Proceedings
EditorsRuben Vera-Rodriguez, Julian Fierrez, Aythami Morales
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783030134686
StatePublished - 2019
Event23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018 - Madrid, Spain
Duration: 19 Nov 201822 Nov 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11401 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018


  • Person re-identification
  • Spatial stream
  • Temporal stream


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