A frontal view gait recognition based on 3D imaging using a time of flight camera

Tengku Afendi, Fatih Kurugollu, Danny Crookes, Ahmed Bouridane

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)

Abstract

Studies have been carried out to recognize individuals from a frontal view using their gait patterns. In previous work, gait sequences were captured using either single or stereo RGB camera systems or the Kinect 1.0 camera system. In this research, we used a new frontal view gait recognition method using a laser based Time of Flight (ToF) camera. In addition to the new gait data set, other contributions include enhancement of the silhouette segmentation, gait cycle estimation and gait image representations. We propose four new gait image representations namely Gait Depth Energy Image (GDE), Partial GDE (PGDE), Discrete Cosine Transform GDE (DGDE) and Partial DGDE (PDGDE). The experimental results show that all the proposed gait image representations produce better accuracy than the previous methods. In addition, we have also developed Fusion GDEs (FGDEs) which achieve better overall accuracy and outperform the previous methods.
Original languageEnglish
Publication statusPublished - 2014
Event22nd European Signal Processing Conference, EUSIPCO 2014 - Lisbon, Portugal
Duration: 1 Jan 2014 → …

Conference

Conference22nd European Signal Processing Conference, EUSIPCO 2014
Period1/01/14 → …

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