Automatic Recognition by Gait

Nixon, Mark S.; Carter, J.N.

doi:10.1109/jproc.2006.886018

Cited by 203 publications

(59 citation statements)

References 45 publications

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“…In the second half, once the weight has been passed onto the other limb, the hip flexes in preparation for the swing phase. As such, the specific points such as joints also show sinusoidal variation in position [22]. Further, the plane of human view varies by about ± 15 degrees when walking.…”

Section: A Gait Feature Extractionmentioning

confidence: 98%

On using gait biometrics to enhance face pose estimation

Jung

Nixon

2010

2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS)

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Abstract-Many face biometrics systems use controlled environments where subjects are viewed directly facing the camera. This is less likely to occur in surveillance environments, so a process is required to handle the pose variation of the human head, change in illumination, and low frame rate of input image sequences. This has been achieved using scale invariant features and 3D models to determine the pose of the human subject. Then, a gait trajectory model is generated to obtain the correct the face region whilst handing the looming effect. In this way, we describe a new approach aimed to estimate accurate face pose. The contributions of this research include the construction of a 3D model for pose estimation from planar imagery and the first use of gait information to enhance the face pose estimation process.

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Section: A Gait Feature Extractionmentioning

confidence: 98%

On using gait biometrics to enhance face pose estimation

Jung

Nixon

2010

2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS)

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“…We refer the readers to (94,95) for surveys of model-based and model-free approaches at a relatively early research stage. The model-free approaches derive the human silhouette by separating the moving object from the background.…”

Section: Approaches To Gait Recognitionmentioning

confidence: 99%

Gait Recognition: Databases, Representations, and Applications

Makihara

Matovski

Nixon

et al. 2015

Wiley Encyclopedia of Electrical and Electronics Engineering

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There has been considerable progress in automatic recognition of people by the way they walk since its inception almost 20 years ago: there is now a plethora of technique and data which continue to show that a person's walking is indeed unique. Gait recognition is a behavioural biometric which is available even at a distance from a camera when other biometrics may be occluded, obscured or suffering from insufficient image resolution (e.g. a blurred face image or a face image occluded by mask). Since gait recognition does not require subject cooperation due to its non-invasive capturing process, it is expected to be applied for criminal investigation from CCTV footages in public and private spaces. This article introduces current progress, a research background, and basic approaches for gait recognition in the first three sections, and two important aspects of gait recognition, the gait databases and gait feature representations are described in the following sections.Publicly available gait databases are essential for benchmarking individual approaches, and such databases should contain a sufficient number of subjects as well as covariate factors to realize statistically reliable performance evaluation and also robust gait recognition. Gait recognition researchers have therefore built such useful gait databases which incorporate subject diversities and/or rich covariate factors.Gait feature representation is also an important aspect for effective and efficient gait recognition. We describe the two main approaches to representation: model-free (appearance-based) approaches and model-based approaches. In particular, silhouette-based model-free approaches predominate in recent studies and many have been proposed and are described in detail.Performance evaluation results of such recent gait feature representations on two of the publicly available gait databases are reported: USF Human ID with rich covariate factors such as views, surface, bag, shoes, time elapse; and OU-ISIR LP with more than 4,000 subjects. Since gait recognition is suitable for criminal investigation applications of the gait recognition to forensics are addressed with real criminal cases in the application section. Finally, several open problems of the gait recognition are discussed to show future research avenues of the gait recognition.

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“…These methods cannot reliably recognize non cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages [1], [2]. There is a rich literature, including medical and psychological studies, indicating the potential for gait in personal identification [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Human Perambulation as a Self Calibrating Biometric

Goffredo

Spencer

Pearce

et al.

Analysis and Modeling of Faces and Gestures

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Abstract. This paper introduces a novel method of single camera gait reconstruction which is independent of the walking direction and of the camera parameters. Recognizing people by gait has unique advantages with respect to other biometric techniques: the identification of the walking subject is completely unobtrusive and the identification can be achieved at distance. Recently much research has been conducted into the recognition of frontoparallel gait. The proposed method relies on the very nature of walking to achieve the independence from walking direction. Three major assumptions have been done: human gait is cyclic; the distances between the bone joints are invariant during the execution of the movement; and the articulated leg motion is approximately planar, since almost all of the perceived motion is contained within a single limb swing plane. The method has been tested on several subjects walking freely along six different directions in a small enclosed area. The results show that recognition can be achieved without calibration and without dependence on view direction. The obtained results are particularly encouraging for future system development and for its application in real surveillance scenarios.

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Automatic Recognition by Gait

Cited by 203 publications

References 45 publications

On using gait biometrics to enhance face pose estimation

On using gait biometrics to enhance face pose estimation

Gait Recognition: Databases, Representations, and Applications

Human Perambulation as a Self Calibrating Biometric

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