Biomechanical metrics of aesthetic perception in dance

Bronner, Shaw; Shippen, James

doi:10.1007/s00221-015-4424-4

Cited by 33 publications

(39 citation statements)

References 74 publications

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“…It is therefore particularly well suited for analysing the correlated patterns of segment movements that constitute "technique" in sports (Witte, Ganter, Baumgart, & Peham, 2010). PCA has already been applied for technique analysis in dance (Bronner & Shippen, 2015), diving (Young & Reinkensmeyer, 2014), gymnastics (G. K. Williams et al, 2016), juggling (Huys, Daffertshofer, & Beek, 2004), walking and running (Dona, Preatoni, Cobelli, Rodano, & Harrison, 2009;Lamoth, Daffertshofer, Huys, & Beek, 2009), skiing (Federolf et al, 2014), soccer (Diaz, Fajen, & Phillips, 2012) and tennis (Huys, Smeeton, Hodges, Beek, & Wiliams, 2008;Smeeton & Huys, 2011). However, an important limitation in many of the previous analyses is that separate PCAs were calculated for each individual participant.…”

Section: Introductionmentioning

confidence: 99%

Technique analysis in elite athletes using principal component analysis

Gløersen

Myklebust

Hallén

et al. 2017

Journal of Sports Sciences

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The aim of this study was to advance current movement analysis methodology to enable a technique analysis in sports facilitating (1) concurrent comparison of the techniques between several athletes; (2) identification of potentially beneficial technique modifications and (3) a visual representation of the findings for feedback to the athletes. Six elite cross-country skiers, three world cup winners and three national elite, roller ski skated using the V2 technique on a treadmill while their movement patterns were recorded using 41 reflective markers. A principal component analysis performed on the marker positions resulted in multi-segmental "principal" movement components (PMs). A novel normalisation facilitated comparability of the PMs between athletes. Additionally, centre of mass (COM) trajectories were modelled. We found correlations between the athletes' performance levels (judged from race points) and specific features in the PMs and in the COM trajectories. Plausible links between COM trajectories and PMs were observed, suggesting that better performing skiers exhibited a different, possibly more efficient use of their body mass for propulsion. The analysis presented in the current study revealed specific technique features that appeared to relate to the skiers' performance levels. How changing these features would affect an individual athlete's technique was visualised with animated stick figures.

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Section: Introductionmentioning

confidence: 99%

Technique analysis in elite athletes using principal component analysis

Gløersen

Myklebust

Hallén

et al. 2017

Journal of Sports Sciences

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“…PCA has been used in the past three decades as an efficient method of defining the essential, i.e., collective, variables in a range of complex dynamical processes such as protein folding (Matsunaga et al, 2007 ; Hayward and De Groot, 2008 ; Maisuradze et al, 2009 ) and brain dynamics (Jirsa et al, 2002 ). In sport science, PCA has allowed identifying the performance of an interpersonal precision task (Ramenzoni et al, 2012 ) to determine the impact of different training programs on cardio-respiratory coordination (Balagué et al, 2016 ), and to identify different dancing coordination patterns depending on concrete task constraints (Bronner and Shippen, 2015 ; Torrents et al, 2015 ). In soccer, PCA has been applied to capture player positional patterns and their variability (Barros et al, 2006 ).…”

Section: Introductionmentioning

confidence: 99%

Soft-Assembled Multilevel Dynamics of Tactical Behaviors in Soccer

et al. 2016

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This study aimed to identify the tactical patterns and the timescales of variables during a soccer match, allowing understanding the multilevel organization of tactical behaviors, and to determine the similarity of patterns performed by different groups of teammates during the first and second halves. Positional data from 20 professional male soccer players from the same team were collected using high frequency global positioning systems (5 Hz). Twenty-nine categories of tactical behaviors were determined from eight positioning-derived variables creating multivariate binary (Boolean) time-series matrices. Hierarchical principal component analysis (PCA) was used to identify the multilevel structure of tactical behaviors. The sequential reduction of each set level of principal components revealed a sole principal component as the slowest collective variable, forming the global basin of attraction of tactical patterns during each half of the match. In addition, the mean dwell time of each positioning-derived variable helped to understand the multilevel organization of collective tactical behavior during a soccer match. This approach warrants further investigations to analyze the influence of task constraints on the emergence of tactical behavior. Furthermore, PCA can help coaches to design representative training tasks according to those tactical patterns captured during match competitions and to compare them depending on situational variables.

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“…where j i = [ r, ψ q , ψ д , ϕ д ] T is jerk and angular jerk. We minimize jerk since it provides a commonly used metric to quantify smoothness [Hogan 1984] and is known to be a decisive factor for the aesthetic perception of motion [Bronner and Shippen 2015]. This cost term again implicitly effects θ by only allowing it to progress such that the quadrotor motion following the reference path f d (θ ) is smooth according to (9).…”

Section: Smooth Progressmentioning

confidence: 99%

Optimizing for aesthetically pleasing quadrotor camera motion

2018

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Fig. 1. Quadrotor camera tools generate trajectories based on user-specified keyframes in time and space. Reasoning about spatio-temporal distances is hard for users and can lead to visually unappealing results and fluctuating camera velocities. Top row: user-specified keyframes (blue) are positioned in time, such that the camera first moves too slow and then needs to accelerate drastically to reach the specified end-point. Bottom row: results of our method which automatically positions keyframes (blue) in time such that the camera moves smoothly over the entire trajectory (illustrative example).In this paper we first contribute a large scale online study (N ≈ 400) to better understand aesthetic perception of aerial video. The results indicate that it is paramount to optimize smoothness of trajectories across all keyframes. However, for experts timing control remains an essential tool. Satisfying this dual goal is technically challenging because it requires giving up desirable properties in the optimization formulation. Second, informed by this study we propose a method that optimizes positional and temporal reference fit jointly. This allows to generate globally smooth trajectories, while retaining user control over reference timings. The formulation is posed as a variable, infinite horizon, contour-following algorithm. Finally, a comparative lab study indicates that our optimization scheme outperforms the state-of-theart in terms of perceived usability and preference of resulting videos. For novices our method produces smoother and better looking results and also experts benefit from generated timings.

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Biomechanical metrics of aesthetic perception in dance

Cited by 33 publications

References 74 publications

Technique analysis in elite athletes using principal component analysis

Technique analysis in elite athletes using principal component analysis

Soft-Assembled Multilevel Dynamics of Tactical Behaviors in Soccer

Optimizing for aesthetically pleasing quadrotor camera motion

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