The Effect of PETTLEP Imagery in a Pre- Shot Routine on Full Swing Golf Shot Accuracy: A Single Subject Design

Imagery has been shown to be an effective tool for enhancing performance in a variety of sports, specifically in golf. The purpose of this study was to investigate the effect of a PETTLEP imagery intervention, implemented into a pre-shot routine, on a full swing golf shot. A single subjects design was used with three conditions: imagery before pre-shot routine, imagery after pre-shot routine, and withdrawal from intervention. A control condition was included for comparison with illuminate the possible effects of practice. Participants were nine undergraduate volunteers with an average age of 19.3 years and an average golf score of 82.1. Three sets of data were recorded: total score, balls in A1 (the closest area), and balls in A5 (outside of the grid). When comparing control means: the intervention phase (M = 29.15) decreased in total score from baseline (M = 33.85), and withdrawal (M = 33.8). All imagery participants improved from baseline (M = 42.25) to intervention (M= 48.1), to withdrawal (M= 47.75). There was no apparent difference in imagery time, before or after the pre-shot routine. Implications from this study may benefit golfers and sport psychology consultants working with golfers.

[1]  Hong-Jiang Zhang.  Relevance Feedback in Content-Based Image Retrieval , 2003 .

[2]  Thomas S. Huang,et al.  A novel relevance feedback technique in image retrieval , 1999, MULTIMEDIA '99.

[3]  Chi-Ren Shyu,et al.  Relevance feedback decision trees in content-based image retrieval , 2000, 2000 Proceedings Workshop on Content-based Access of Image and Video Libraries.

[4]  Calvin C. Gotlieb,et al.  Texture descriptors based on co-occurrence matrices , 1990, Comput. Vis. Graph. Image Process..

[5]  Bo Zhang,et al.  An efficient and effective region-based image retrieval framework , 2004, IEEE Transactions on Image Processing.

[6]  Thomas S. Huang,et al.  Relevance feedback: a power tool for interactive content-based image retrieval , 1998, IEEE Trans. Circuits Syst. Video Technol..

[7]  Patrick Haffner,et al.  Support vector machines for histogram-based image classification , 1999, IEEE Trans. Neural Networks.

[8]  Joost van de Weijer,et al.  Boosting color saliency in image feature detection , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Pietro Perona,et al.  Is bottom-up attention useful for object recognition? , 2004, CVPR 2004.

[10]  C. Skinner,et al.  Decreasing Putting Yips in Accomplished Golfers via Solution-Focused Guided Imagery: A Single-Subject Research Design , 2009 .

[11]  James Ze Wang,et al.  Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  J. Wolfe,et al.  What attributes guide the deployment of visual attention and how do they do it? , 2004, Nature Reviews Neuroscience.

[13]  Alessandro Sperduti,et al.  Supervised neural networks for the classification of structures , 1997, IEEE Trans. Neural Networks.

[14]  Davide Corso,et al.  Morphological analysis of textured images for identification of thin structures , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[15]  Laurent Itti,et al.  Automatic foveation for video compression using a neurobiological model of visual attention , 2004, IEEE Transactions on Image Processing.

[16]  Robert M. Gray,et al.  Multiresolution image classification by hierarchical modeling with two-dimensional hidden Markov models , 2000, IEEE Trans. Inf. Theory.

[17]  C. Wright,et al.  The effect of PETTLEP imagery on strength performance , 2009 .

[18]  Shih-Fu Chang,et al.  Transform features for texture classification and discrimination in large image databases , 1994, Proceedings of 1st International Conference on Image Processing.

[19]  C. Wakefield,et al.  Impact of Differing Frequencies of PETTLEP Imagery on Netball Shooting Performance , 2009 .

[20]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[21]  Bir Bhanu,et al.  Active concept learning in image databases , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[22]  Malay Kumar Kundu,et al.  Edge based features for content based image retrieval , 2003, Pattern Recognit..

[23]  M. Jeannerod.  TO ACT OR NOT TO ACT : PERSPECTIVES ON THE REPRESENTATION OF ACTIONS , 1999 .

[24]  John K. Tsotsos,et al.  Modeling Visual Attention via Selective Tuning , 1995, Artif. Intell..

[25]  Takashi Matsuyama,et al.  Multiobject Behavior Recognition by Event Driven Selective Attention Method , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Chi-Man Pun,et al.  Log-Polar Wavelet Energy Signatures for Rotation and Scale Invariant Texture Classification , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[28]  Pietro Perona,et al.  One-shot learning of object categories , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[29]  Pieter R. Roelfsema,et al.  Object-based attention in the primary visual cortex of the macaque monkey , 1998, Nature.

[30]  John G. Daugman,et al.  Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..

[31]  Wei-Ying Ma,et al.  Learning a semantic space from user's relevance feedback for image retrieval , 2003, IEEE Trans. Circuits Syst. Video Technol..

[32]  Jens Michael Carstensen,et al.  Density-based retrieval from high-similarity image databases , 2004, Pattern Recognit..

[33]  Sven J. Dickinson,et al.  Active Object Recognition Integrating Attention and Viewpoint Control , 1997, Comput. Vis. Image Underst..

[34]  Aynsley M. Smith,et al.  A Multidisciplinary Study of the ‘Yips’ Phenomenon in Golf , 2000, Sports medicine.

[35]  Gerard Salton,et al.  A vector space model for automatic indexing , 1975, CACM.

[36]  David A. Forsyth,et al.  Matching Words and Pictures , 2003, J. Mach. Learn. Res..

[37]  Wenyin Liu,et al.  Joint semantics and feature based image retrieval using relevance feedback , 2003, IEEE Trans. Multim..

[38]  B. S. Manjunath,et al.  Unsupervised Segmentation of Color-Texture Regions in Images and Video , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[39]  J. Crossman,et al.  Effects of a Cognitive Intervention Package on the Free-Throw Performance of Varsity Basketball Players during Practice and Competition , 1992, Perceptual and motor skills.

[40]  Christoph Goller,et al.  Learning task-dependent distributed representations by backpropagation through structure , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

[41]  W. Eric L. Grimson,et al.  Spatial template extraction for image retrieval by region matching , 2003, IEEE Trans. Image Process..

[42]  Jeremy M. Wolfe,et al.  The Level of Attention: Mediating Between the Stimulus and Perception , 2003 .

[43]  Weisi Lin,et al.  Modeling visual attention's modulatory aftereffects on visual sensitivity and quality evaluation , 2005, IEEE Transactions on Image Processing.

[44]  Jesse S. Jin,et al.  Combining intra-image and inter-class semantics for consumer image retrieval , 2005, Pattern Recognit..

[45]  Nicolai Petkov,et al.  Comparison of texture features based on Gabor filters , 2002, IEEE Trans. Image Process..

[46]  Claire Calmels,et al.  Effects of an Imagery Training Program on Selective Attention of National Softball Players , 2004 .

[47]  Lie Lu,et al.  A generic framework of user attention model and its application in video summarization , 2005, IEEE Trans. Multim..

[48]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[49]  M.L. Miller,et al.  Hidden annotation in content based image retrieval , 1997, 1997 Proceedings IEEE Workshop on Content-Based Access of Image and Video Libraries.

[50]  Jianping Fan,et al.  Statistical modeling and conceptualization of natural images , 2005, Pattern Recognit..

[51]  J.A. Taylor,et al.  The effects of outcome imagery on golf-putting performance , 2002, Journal of sports sciences.

[52]  Bir Bhanu,et al.  Integrating relevance feedback techniques for image retrieval using reinforcement learning , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[53]  Hyeran Byun,et al.  FRIP: a region-based image retrieval tool using automatic image segmentation and stepwise Boolean AND matching , 2005, IEEE Transactions on Multimedia.

[54]  Craig R. Hall,et al.  The Relationship of Skill Level and Age to the Use of Imagery by Golfers , 2006 .

[55]  Gerard J. Fogarty,et al.  Psychological skills training in golf: the role of individual differences in cognitive preferences , 1997 .

[56]  Dennis F. Dunn,et al.  Optimal Gabor filters for texture segmentation , 1995, IEEE Trans. Image Process..

[57]  Robert Dolejší.  The Second Study , 1939 .

[58]  M. Jeannerod.  The 25th Bartlett Lecture , 1999 .

[59]  William E. Higgins,et al.  Integrated approach to texture segmentation using multiple Gabor filters , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[60]  Stefanos D. Kollias,et al.  Invariant image classification using triple-correlation-based neural networks , 1994, IEEE Trans. Neural Networks.

[61]  Jean M. Williams.  Applied Sport Psychology , 2005 .

[62]  William Nick Street,et al.  Cluster-driven refinement for content-based digital image retrieval , 2004, IEEE Transactions on Multimedia.

[63]  Zheru Chi,et al.  Structured-Based Neural Network Classification of Images Using Wavelet Coefficients , 2006, ISNN.

[64]  G. Martin,et al.  Applied research studies with single-subject designs: Why so few? , 1996 .

[65]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

[66]  Jiri Matas,et al.  The Multimodal Neighborhood Signature for Modeling Object Color Appearance and Applications in Object Recognition and Image Retrieval , 2002, Comput. Vis. Image Underst..

[67]  C. Molinaro,et al.  Mental Imagery Combined with Physical Practice of Approach Shots for Golf Beginners , 2005, Perceptual and motor skills.

[68]  Robert J. Rotella,et al.  Golf is Not a Game of Perfect , 1995 .

[69]  Hagit Hel-Or,et al.  Symmetry as a Continuous Feature , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[70]  Michael Spittle,et al.  Imagery in Sport , 2005, Sport & Exercise Psychology Review.

[71]  Sugata Ghosal,et al.  An image retrieval system with automatic query modification , 2002, IEEE Trans. Multim..

[72]  Jack Nicklaus.  Golf My Way , 1974 .

[73]  John S. Partington,et al.  Mental Links to Excellence , 1988 .

[74]  M. Bar.  Visual objects in context , 2004, Nature Reviews Neuroscience.

[75]  N. Kanwisher,et al.  Visual attention: Insights from brain imaging , 2000, Nature Reviews Neuroscience.

[76]  B. S. Manjunath,et al.  NeTra: A toolbox for navigating large image databases , 1997, Multimedia Systems.

[77]  P. Holmes,et al.  The effect of imagery modality on golf putting performance , 2004 .

[78]  C.-C. Jay Kuo,et al.  Texture analysis and classification with tree-structured wavelet transform , 1993, IEEE Trans. Image Process..

[79]  Robert M. Gray,et al.  Image classification by a two-dimensional hidden Markov model , 2000, IEEE Trans. Signal Process..

[80]  Leonidas J. Guibas,et al.  A metric for distributions with applications to image databases , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[81]  R. Rosenthal,et al.  Pygmalion in the Classroom: Teacher Expectation and Pupils' Intellectual Development , 1968 .

[82]  Daniel R. Czech,et al.  The Effects of Video and Cognitive Imagery on Throwing Performance of Baseball Picthers: A Single Subjects Design , 2008 .

[83]  Craig A. Wrisberg,et al.  The Effects of Multisensory Imagery in Conjunction with Physical Movement Rehearsal on Golf Putting Performance , 2006 .

[84]  Alessandro Sperduti,et al.  A general framework for adaptive processing of data structures , 1998, IEEE Trans. Neural Networks.

[85]  Michael Lindenbaum,et al.  Attention-based dynamic visual search using inner-scene similarity: algorithms and bounds , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[86]  Edward Y. Chang,et al.  CBSA: content-based soft annotation for multimodal image retrieval using Bayes point machines , 2003, IEEE Trans. Circuits Syst. Video Technol..

[87]  Yixin Chen,et al.  A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[88]  P. Cohen,et al.  Partition filters: a new class of morphological operators for segmenting textured images , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[89]  Georgios S. Paschos,et al.  Perceptually uniform color spaces for color texture analysis: an empirical evaluation , 2001, IEEE Trans. Image Process..

[90]  Dan Roth,et al.  Learning to detect objects in images via a sparse, part-based representation , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[91]  David A. Forsyth,et al.  Learning the semantics of words and pictures , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[92]  C. T. Hayashi.  Foundations of Sport and Exercise Psychology , 1998 .

[93]  Longin Jan Latecki,et al.  The choice of vantage objects for image retrieval , 2003, Pattern Recognit..

[94]  Z. Chi,et al.  Plant species recognition based on bark patterns using novel Gabor filter banks , 2003, International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003.

[95]  S. Murphy,et al.  The effects of positive and negative imagery on motor skill performance , 1985, Cognitive Therapy and Research.

[96]  Tat-Seng Chua,et al.  A learning-based approach for annotating large on-line image collection , 2004, 10th International Multimedia Modelling Conference, 2004. Proceedings..

[97]  Bärbel Mertsching,et al.  Data- and Model-Driven Gaze Control for an Active-Vision System , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[98]  Ah Chung Tsoi,et al.  Content-Based Image Retrieval with Relevance Feedback Using Adaptive Processing of Tree-Structure Image Representation , 2003, Int. J. Image Graph..

[99]  B. S. Manjunath,et al.  Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[100]  Craig A. Wrisberg,et al.  APPLIED RESEARCH – The Effect of Cognitive Strategies on the Free Throw Shooting Performance of Young Athletes , 1989 .

[101]  J Theeuwes,et al.  Visual selective attention: a theoretical analysis. , 1993, Acta psychologica.

[102]  C. Hall,et al.  The effect of an imagery training program on imagery ability, imagery use, and figure skating performance , 1991 .

[103]  Sven Loncaric,et al.  A survey of shape analysis techniques , 1998, Pattern Recognit..

[104]  Yasufumi Takama,et al.  Mathematical aggregation operators in image retrieval: effect on retrieval performance and role in relevance feedback , 2005, Signal Process..

[105]  S. Bray,et al.  Pre-competition imagery, self-efficacy and performance in collegiate golfers , 2001, Journal of sports sciences.

[106]  S. Bull,et al.  The use of a single-case research design to investigate the efficacy of imagery training , 1996 .

[107]  Dave Smith,et al.  It's All in the Mind: PETTLEP-Based Imagery and Sports Performance , 2007 .

[108]  Jitendra Malik,et al.  Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[109]  Craig R. Hall,et al.  The use of imagery by rowers. , 1992 .

[110]  Fabio Roli,et al.  Bayesian relevance feedback for content-based image retrieval , 2004, Pattern Recognit..

[111]  Ken Nakayama,et al.  Attentional requirements in a ‘preattentive’ feature search task , 1997, Nature.

[112]  Michael G. Strintzis,et al.  Region-Based Image Retrieval Using an Object Ontology and Relevance Feedback , 2004, EURASIP J. Adv. Signal Process..

[113]  Shamik Sural,et al.  Segmentation and histogram generation using the HSV color space for image retrieval , 2002, Proceedings. International Conference on Image Processing.

[114]  Wei-Ying Ma,et al.  A novel region-based image retrieval method using relevance feedback , 2001, MULTIMEDIA '01.

[115]  Patrick Le Callet,et al.  A coherent computational approach to model bottom-up visual attention , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[116]  Zheru Chi,et al.  Genetic evolution processing of data structures for image classification , 2005, IEEE Transactions on Knowledge and Data Engineering.

[117]  Remco Polman,et al.  The Effects of Individualized Imagery Interventions on Golf Performance and Flow States , 2005 .

[118]  Allan Collins,et al.  A spreading-activation theory of semantic processing , 1975 .

[119]  Gunther Heidemann,et al.  Focus-of-attention from local color symmetries , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[120]  S Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

[121]  Dave Smith,et al.  Beating the Bunker , 2008, Research quarterly for exercise and sport.

[122]  Jonathon S. Hare,et al.  Salient Regions for Query by Image Content , 2004, CIVR.

[123]  Laurence G. Hassebrook,et al.  A multistage, optimal active contour model , 1996, IEEE Trans. Image Process..

[124]  J. Pates,et al.  An Investigation into the Effects of Hypnosis on Basketball Performance , 2001 .

[125]  Ricardo Weigert Coelho,et al.  Imagery Intervention in Open and Closed Tennis Motor Skill Performance , 2007, Perceptual and motor skills.

[126]  M. E. Boyle.  Single Case Experimental Designs: Strategies for Studying Behavior Change , 1983 .

[127]  Wei-Ying Ma,et al.  Information embedding based on user's relevance feedback for image retrieval , 1999, Optics East.

[128]  P. Holmes,et al.  The PETTLEP Approach to Motor Imagery: A Functional Equivalence Model for Sport Psychologists , 2001 .

[129]  Kosuke Sato,et al.  Real-time gesture recognition by learning and selective control of visual interest points , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[130]  Roland T. Chin,et al.  Deformable Contours: Modeling and Extraction , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[131]  Hideyuki Tamura,et al.  Textural Features Corresponding to Visual Perception , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[132]  Lei Guo,et al.  Automatic attention object extraction from images , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[133]  Christof Koch,et al.  Modeling attention to salient proto-objects , 2006, Neural Networks.

[134]  M. Arvinen-Barrow,et al.  Elite and Novice Athletes' Imagery Use in Open and Closed Sports , 2007 .

[135]  Shaoping Ma,et al.  Using Bayesian classifier in relevant feedback of image retrieval , 2000, Proceedings 12th IEEE Internationals Conference on Tools with Artificial Intelligence. ICTAI 2000.

[136]  D. Lavallee,et al.  The effect of pre-shot routines on golf wedge shot performance , 2001 .

[137]  Luc Van Gool,et al.  Moment invariants for recognition under changing viewpoint and illumination , 2004, Comput. Vis. Image Underst..

[138]  Fuhui Long,et al.  Fundamentals of Content-Based Image Retrieval , 2003 .

[139]  C. Hall,et al.  The Use of Imagery by Athletes in Selected Sports , 1990 .

[140]  Shaoping Ma,et al.  Relevance feedback in content-based image retrieval: Bayesian framework, feature subspaces, and progressive learning , 2003, IEEE Trans. Image Process..

[141]  L. Jones,et al.  An imagery intervention during the competitive season with an elite rugby union player , 2004 .

[142]  James Ze Wang,et al.  SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[143]  G. Deco,et al.  A hierarchical neural system with attentional top–down enhancement of the spatial resolution for object recognition , 2000, Vision Research.

[144]  Michael Scott Shivetts.  Effects of an Individual Goal-Setting Intervention on Goal Orientation, Self-Confidence, and Riving Accuracy in Average Golfers: A Quantitative Design , 2006 .

[145]  Luo Si,et al.  Effective automatic image annotation via a coherent language model and active learning , 2004, MULTIMEDIA '04.

[146]  Dave Smith,et al.  The Effect of a Short-term PETTLEP Imagery Intervention on a Cognitive Task , 2007 .

[147]  Hemant D. Tagare,et al.  A Maximum-Likelihood Strategy for Directing Attention during Visual Search , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[148]  Chun-Jen Tsai,et al.  Visual sensitivity guided bit allocation for video coding , 2006, IEEE Transactions on Multimedia.

[149]  James Lee Hafner,et al.  Efficient Color Histogram Indexing for Quadratic Form Distance Functions , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[150]  Kanad K. Biswas,et al.  Region-based image retrieval using integrated color, shape, and location index , 2004, Comput. Vis. Image Underst..

[151]  Bo Zhang,et al.  Relevance feedback in region-based image retrieval , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[152]  Zheru Chi,et al.  Fuzzy integral for leaf image retrieval , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[153]  C. Hall,et al.  The effects of internal and external imagery on performing figures in figure skating. , 1985, Canadian journal of applied sport sciences. Journal canadien des sciences appliquees au sport.

[154]  A. Baddeley.  Essentials of Human Memory , 1999 .

[155]  Atilla Baskurt,et al.  Object of interest-based visual navigation, retrieval, and semantic content identification system , 2004, Comput. Vis. Image Underst..

[156]  Tsuhan Chen,et al.  An active learning framework for content-based information retrieval , 2002, IEEE Trans. Multim..

[157]  Rama Chellappa,et al.  Separability-based multiscale basis selection and feature extraction for signal and image classification , 1998, IEEE Trans. Image Process..