Gait Recognition from a Single Image Using a Phase-Aware Gait Cycle Reconstruction Network

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12364)


We propose a method of gait recognition just from a single image for the first time, which enables latency-free gait recognition. To mitigate large intra-subject variations caused by a phase (gait pose) difference between a matching pair of input single images, we first reconstruct full gait cycles of image sequences from the single images using an auto-encoder framework, and then feed them into a state-of-the-art gait recognition network for matching. Specifically, a phase estimation network is introduced for the input single image, and the gait cycle reconstruction network exploits the estimated phase to mitigate the dependence of an encoded feature on the phase of that single image. This is called phase-aware gait cycle reconstructor (PA-GCR). In the training phase, the PA-GCR and recognition network are simultaneously optimized to achieve a good trade-off between reconstruction and recognition accuracies. Experiments on three gait datasets demonstrate the significant performance improvement of this method.


Gait cycle reconstruction Gait recognition Single image 



This work was supported by JSPS KAKENHI Grant No. JP18H04115, JP19H05692, and JP20H00607, Jiangsu Provincial Science and Technology Support Program (No. BE2014714), the 111 Project (No. B13022), and the Priority Academic Program Development of Jiangsu Higher Education Institutions.


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Nanjing University of Science and TechnologyNanjingChina
  2. 2.ISIR, Osaka UniversityOsakaJapan

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