6,043 research outputs found
On gait as a biometric: progress and prospects
No full textThere is increasing interest in automatic recognition by gait given its unique capability to recognize people at a distance when other biometrics are obscured. Application domains are those of any noninvasive biometric, but with particular advantage in surveillance scenarios. Its recognition capability is supported by studies in other domains such as medicine (biomechanics), mathematics and psychology which also suggest that gait is unique. Further, examples of recognition by gait can be found in literature, with early reference by Shakespeare concerning recognition by the way people walk. Many of the current approaches confirm the early results that suggested gait could be used for identification, and now on much larger databases. This has been especially influenced by DARPA’s Human ID at a Distance research program with its wide scenario of data and approaches. Gait has benefited from the developments in other biometrics and has led to new insight particularly in view of covariates. Equally, gait-recognition approaches concern extraction and description of moving articulated shapes and this has wider implications than just in biometrics
Advances in Automatic Gait Recognition
No full textAutomatic recognition by gait is subject to increasing interest and has the unique capability to recognize people at a distance when other biometrics are obscured. Its interest is reinforced by the longstanding computer vision interest in automated non-invasive analysis of human motion. Its recognition capability is supported by studies in other domains such as medicine (biomechanics), mathematics and psychology which continue to suggest that gait is unique. Further, examples of recognition by gait can be found in literature, with early reference by Shakespeare concerning recognition by the way people walk. Current approaches confirm the early results that suggested gait could be used for identification, and now on much larger databases. This has been especially influenced by the Human ID at a Distance research program with its wide scenario of data and approaches. Gait has benefited from the developments in other biometrics and has led to new insight particularly in view of covariates. As such, gait is an interesting research area, with contributions not only to the field of biometrics but also to the stock of new techniques for the extraction and description of objects moving within image sequences
The authors respond: Issues surrounding reliability, quality, and practicality with timed-reading assessments: Expanding on Carter et al.’s (2023) a unitary measure of L2 silent reading fluency accounting for comprehension
No full textCarter et al. (2023) presented empirical evidence in support of a proposed new measure of L2 silent reading fluency. Referencing their method, this article addresses three separate practical issues related to using timed readings (TRs) to foster L2 reading fluency: TR assessment reliability, quality, and practicality. One seeming limitation of Carter et al.’s (2023) method was the relatively low reliability of three separate TR quizzes used in their study on reading fluency. However, considering that the interpretation and use of reliability estimates should be context-dependent, we argue that the standard expectations of 0.8 or higher may be simply unrealistic given the unique constraints surrounding timed readings. Furthermore, reliability is only one facet of a validity argument and intentional changes aimed at increasing reliability may, at times, come at the expense of other important aspects of validity. This article also offers practical advice for constructing effective TR quiz questions and directs the reader to tools for tracking student readers’ reading fluency progress
A middleware for a large array of cameras
No full textLarge arrays of cameras are increasingly being employed for producing high quality image sequences needed for motion analysis research. This leads to the logistical problem with coordination and control of a large number of cameras. In this paper, we used a lightweight multi-agent system for coordinating such camera arrays. The agent framework provides more than a remote sensor access API. It allows reconfigurable and transparent access to cameras, as well as software agents capable of intelligent processing. Furthermore, it eases maintenance by encouraging code reuse. Additionally, our agent system includes an automatic discovery mechanism at startup, and multiple language bindings. Performance tests showed the lightweight nature of the framework while validating its correctness and scalability. Two different camera agents were implemented to provide access to a large array of distributed cameras. Correct operation of these camera agents was confirmed via several image processing agents
Assessment of the statistical relevance of TR-PIV datasets
No full textThe increasing interest for high repetition rate global optical measurement techniques such as Time-Resolved Particle Image Velocimetry (TR-PIV) raises a number of questions concerning their ability to provide relevant statistical and spectral quantities. In an effort to address this issue, complementary TR-PIV and Laser Doppler Velocimetry (LDV) measurements have been carried out. An application to the analysis of the detached flow over a NACA 0015 airfoil at a Reynolds number Re=105 in a water tunnel is proposed
The effect of time on gait recognition performance
No full textMany studies have shown that it is possible to recognize people by the way they walk. However, there are a number of covariate factors that affect recognition performance. The time between capturing the gallery and the probe has been reported to affect recognition the most. To date, no study has shown the isolated effect of time, irrespective of other covariates. Here we present the first principled study that examines the effect of elapsed time on gait recognition. Using empirical evidence we show for the first time that elapsed time does not affect recognition significantly in the short to medium term. By controlling the clothing worn by the subjects and the environment, a Correct Classification Rate (CCR) of 95% has been achieved over 9 months, on a dataset of 2280 gait samples. Our results show that gait can be used as a reliable biometric over time and at a distance. We have created a new multimodal temporal database to enable the research community to investigate various gait and face covariates. We have also investigated the effect of different type of clothes, variations in speed and footwear on the recognition performance. We have demonstrated that clothing drastically affects performance regardless of elapsed time and significantly more than any of the other covariates that we have considered here. The research then suggests a move towards developing appearance invariant recognition algorithms. Thi
Front-view Gait Recognition
No full textWe present a new method for front-view gait biometrics which uses a single non-calibrated camera and extracts unique signatures from descriptors of a silhouette’s deformation. The proposed approach is particularly suitable for identification by gait in the real world, where the advantages of completely unobtrusiveness, remoteness and covertness of the biometric system preclude the availability of camera information and where the CCTV images usually present subjects from an upper front-view. Tests on three different gait databases with subjects walking towards the camera have been performed. The obtained results, with mean CCR of 96:3%, show that gait recognition of individuals observed the front can be achieved without any knowledge of camera parameters. Moreover, the method has been applied to three different walking directions and the results have been compared with the algorithms found in literature. The performance of the proposed system is particularly encouraging for its appliance in surveillance scenarios
Kustverdediging na 1990 (Kustnota 1990): Technisch rapport 11: Strand en duinsuppleties
No full textIn Technisch Rapport 11 (TR 11) wordt een overzicht gegeven van de strand- en duinsuppleties, welke ter compensatie van kusterosie zijn uitgevoerd. In 1988 is het "Handboek zandsuppleties" uitgegeven. Hierin is een schat van gegevens verzameld over het desbetreffende onderwerp. Dit rapport voorziet in een aanvulling op het handboek, met meer recente gegevens. Overlapping van dit rapport met het handboek is zoveel mogelijk vermeden. Naast de aanvulling wordt ingegaan op de levensduur van suppleties en wordt een eerste aanzet gegeven om een puur economische afweging te maken tussen zandsuppleties, die nu een belangrijke maatregel bij kustverdediging zijn, en de bouw van strandhoofden, wat in het verleden een belangrijke maatregel geweest is. Zand wordt met grote drijvende werktuigen relatief goedkoop, als zandwatermengsel, verplaatst. Een netto-verplaatsing van 200.000 tot 500.000 kubieke meter zand per werktuig, per werkweek is haalbaar. Naarmate het zand hoger en verder op de oever gebracht wordt nemen de kosten toe.Kustnot
View Invariant Gait Recognition
No full textRecognition by gait is of particular interest since it is the biometric that is available at the lowest resolution, or when other biometrics are (intentionally) obscured. Gait as a biometric has now shown increasing recognition capability. There are many approaches and these show that recognition can achieve excellent performance on large databases. The majority of these approaches are planar 2D, largely since the early large databases featured subjects walking in a plane normal to the camera view. To extend deployment capability, we need viewpoint invariant gait biometrics. We describe approaches where viewpoint invariance is achieved by 3D approaches or in 2D. In the first group the identification relies on parameters extracted from the 3D body deformation during walking. These methods use several video cameras and the 3D reconstruction is achieved after a camera calibration process. On the other hand, the 2D gait biometric approaches use a single camera, usually positioned perpendicular to the subject’s walking direction. Because in real surveillance scenarios a system that operates in an unconstrained environment is necessary, many of the recent gait analysis approaches are orientated towards viewinvariant gait recognition
Performance Analysis for Gait in Camera Networks
No full textThis paper deploys gait analysis for subject identification in multi-camera surveillance scenarios. We present a new method for viewpoint independent markerless gait analysis that does not require camera calibration and works with a wide range of directions of walking. These properties make the proposed method particularly suitable for gait identification in real surveillance scenarios where people and their behaviour need to be tracked across a set of cameras. Tests on 300 synthetic and real video sequences, with subjects walking freely along different walking directions, have been performed. Since the choice of the cameras' characteristics is a key-point for the development of a smart surveillance system, the performance of the proposed approach is measured with respect to different video properties: spatial resolution, frame-rate, data compression and image quality. The obtained results show that markerless gait analysis can be achieved without any knowledge of camera's position and subject's pose. The extracted gait parameters allow recognition of people walking from different views with a mean recognition rate of 92.2% and confirm that gait can be effectively used for subjects' identification in a multi-camera surveillance scenario
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