A model-based image-matching technique for three-dimensional reconstruction of human motion from uncalibrated video sequences

Krosshaug, Tron; Bahr, Roald

doi:10.1016/j.jbiomech.2004.04.033

Cited by 92 publications

(129 citation statements)

References 29 publications

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“…This approach yielded MBIM based head linear/rotational position measurements every 10 ms (known as a key frame). Similar to Krosshaug and Bahr (2005) {Krosshaug, 2005 #120}, cubic splines were fitted to interpolate between these discrete head linear/rotational position measurements.…”

Section: Vehicle-cadaver Testmentioning

confidence: 99%

Assessment of model-based image-matching for future reconstruction of unhelmeted sport head impact kinematics

Tierney

Joodaki

Krosshaug

et al. 2017

Sports Biomechanics

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Gregory J. Tierney [1] , Hamed Joodaki [2] , Tron Krosshaug [3] , Jason L. Forman [2] , Jeff R. Crandall [2] , Ciaran K. Simms [1] [1] Trinity Centre for Bioengineering, Trinity College Dublin, Ireland [2] Centre for Applied Biomechanics, University of Virginia, United States of America impacts, but velocity data is less reliable. MBIM data, combined in future with velocity/acceleration data from wearable sensors could be used to provide input conditions and evaluate the outputs of multibody and finite element head models for brain injury assessment of sporting head impacts.

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Section: Vehicle-cadaver Testmentioning

confidence: 99%

Assessment of model-based image-matching for future reconstruction of unhelmeted sport head impact kinematics

Tierney

Joodaki

Krosshaug

et al. 2017

Sports Biomechanics

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“…9 41 Although video analysis has the potential to be a more detailed and reliable way of analysing injury mechanism than athlete interviews, current methods for estimating kinematics from uncalibrated video sequences are inadequate. 50 Therefore, the video analysis approach has been more useful for describing the playing situation and athlete/opponent movements than detailed joint biomechanics, although a new model based, image matching technique has recently been described. 50 To date, studies on the mechanisms for ACL injuries have only used simple visual inspection to extract joint kinematic information from video sequences (fig 3).…”

Section: Video Analysismentioning

confidence: 99%

“…In addition, the viewing angle relative to the athlete will determine what variables are most reliable. 50 An important challenge is to determine the exact point of injury. In studies of ACL injuries, one report claims that the ''precise point of injury'' could be determined, 51 whereas another stated that finding the exact moment of ACL disruption was impossible.…”

Section: Video Analysismentioning

confidence: 99%

Research approaches to describe the mechanisms of injuries in sport: limitations and possibilities

Krosshaug

Andersen²,

Olsen³

et al. 2005

Br J Sports Med

169

139

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A number of different methodological approaches have been used to describe the inciting event for sports injuries. These include interviews of injured athletes, analysis of video recordings of actual injuries, clinical studies (clinical findings of joint damage are studied to understand the injury mechanism, mainly through plain radiography, magnetic resonance imaging, arthroscopy, and computed tomography scans), in vivo studies (ligament strain or forces are measured to understand ligament loading patterns), cadaver studies, mathematical modelling and simulation of injury situations, and measurement/estimation from “close to injury” situations. In rare cases, injuries have even occurred during biomechanical experiments. This review describes each research approach and assesses its strengths and weaknesses in contributing to the understanding and prevention of sports injuries.

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“…Using the top view camera and front view camera in Poser, the 180 detailed orientation of the foot segment could be seen and further fine tuning was 181 possible. In the previous validation study of Krosshaug and Bahr (2005) …”

mentioning

confidence: 99%

An ankle joint model-based image-matching motion analysis technique

Mok¹,

Fong²,

Krosshaug³

et al. 2011

Gait & Posture

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1This study presented a model-based image-matching (MBIM) motion analysis 2 technique for ankle joint kinematic measurement. Five cadaveric below-hip 3 specimens were manipulated through a full range of ankle joint motions in bare-foot 4 and shoed conditions. The ankle motions were analyzed by bone-pin marker-based 5 motion analysis and MBIM motion analysis techniques respectively. The root mean 6 square errors of all angles of motion were less than 3 degrees. The average Intraclass 7Correlation Coefficients (ICCs) for the intra-rater reliability were greater than 0.928 8 and the average ICCs for the inter-rater reliability were greater than 0.948 for all 9 ranges of motion. Excellent validity, intra-rater reliability and inter-rater reliability 10 were achieved for the MBIM technique in both bare-foot and shoed conditions. The 11 MBIM technique can therefore provide good estimates of ankle joint kinematics. 12 13

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A model-based image-matching technique for three-dimensional reconstruction of human motion from uncalibrated video sequences

Cited by 92 publications

References 29 publications

Assessment of model-based image-matching for future reconstruction of unhelmeted sport head impact kinematics

Assessment of model-based image-matching for future reconstruction of unhelmeted sport head impact kinematics

Research approaches to describe the mechanisms of injuries in sport: limitations and possibilities

An ankle joint model-based image-matching motion analysis technique

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