skip to main content
research-article

Exploring Biological Motion Regularities of Human Actions: A New Perspective on Video Analysis

Published: 29 June 2017 Publication History

Abstract

The ability to detect potentially interacting agents in the surrounding environment is acknowledged to be one of the first perceptual tasks developed by humans, supported by the ability to recognise biological motion. The precocity of this ability suggests that it might be based on rather simple motion properties, and it can be interpreted as an atomic building block of more complex perception tasks typical of interacting scenarios, as the understanding of non-verbal communication cues based on motion or the anticipation of others’ action goals.
In this article, we propose a novel perspective for video analysis, bridging cognitive science and machine vision, which leverages the use of computational models of the perceptual primitives that are at the basis of biological motion perception in humans.
Our work offers different contributions. In a first part, we propose an empirical formulation for the Two-Thirds Power Law, a well-known invariant law of human movement, and thoroughly discuss its readability in experimental settings of increasing complexity. In particular, we consider unconstrained video analysis scenarios, where, to the best of our knowledge, the invariant law has not found application so far.
The achievements of this analysis pave the way for the second part of the work, in which we propose and evaluate a general representation scheme for biological motion characterisation to discriminate biological movements with respect to non-biological dynamic events in video sequences. The method is proposed as the first layer of a more complex architecture for behaviour analysis and human-machine interaction, providing in particular a new way to approach the problem of human action understanding.

Supplementary Material

a21-noceti-supp.pdf (noceti.zip)
Supplemental movie, appendix, image and software files for, Exploring Biological Motion Regularities of Human Actions: A New Perspective on Video Analysis

References

[1]
J. K. Aggarwal and M. S. Ryoo. 2011. Human activity analysis: A review. ACM Comput. Surv. 43, 3 (April 2011), 16:1--16:43.
[2]
Jake K. Aggarwal and Quin Cai. 1999. Human motion analysis: A review. Comput. Vis. Image Understand. 73, 3 (1999), 428--440.
[3]
A. Casile and M. A. Giese. 2005. Critical features for the recognition of biological motion. J. Vis. 5 (2005), 348--360.
[4]
Claudette Cedras and Mubarak Shah. 1995. Motion-based recognition a survey. Image Vis. Comput. 13, 2 (1995), 129--155.
[5]
Navneet Dalal and Bill Triggs. 2005. Histograms of oriented gradients for human detection. In International Conference on Computer Vision 8 Pattern Recognition, Vol. 2. 886--893.
[6]
Maddalena Fabbri-Destro and Giacomo Rizzolatti. 2008. Mirror neurons and mirror systems in monkeys and humans. Physiology 23, 3 (2008), 171--179.
[7]
S. R. Fanello, I. Gori, G. Metta, and F. Odone. 2013. Keep it simple and sparse: Real-time action recognition. J. Mach. Learn. Res. 14, 1 (2013), 26172640.
[8]
Gunnar Farnebäck. 2003. Two-frame motion estimation based on polynomial expansion. In Proceedings of the 13th Scandinavian Conference on Image Analysis (SCIA’03). 363--370.
[9]
R. Flach, G. Knoblich, and W. Prinz. 2004. The two-thirds power law in motion perception. Vis. Cogn. 11, 4 (2004), 461--481.
[10]
P. H. Greene. 1972. Problems of organization of motor systems. Progr. Theoret. Biol. 2 (1972), 123--145.
[11]
Neville Hogan and Dagmar Sternad. 2007. On rhythmic and discrete movements: Reflections, definitions and implications for motor control. Exp. Brain Res. 181, 1 (2007), 13--30.
[12]
Dongsung Huh and Terrence J Sejnowski. 2015. Spectrum of power laws for curved hand movements. Proc. Natl. Acad. Sci. U.S.A. 112, 29 (2015), E3950--E3958.
[13]
I. T. Jolliffe. 1986. Principal Component Analysis. Springer-Verlag.
[14]
Sonia Kandel, Jean-Pierre Orliaguet, and Paolo Viviani. 2000. Perceptual anticipation in handwriting: The role of implicit motor competence. Percept. Psychophys. 62, 4 (2000), 706--716.
[15]
Chang-Yi Kao and Chin-Shyurng Fahn. 2011. A human-machine interaction technique: Hand gesture recognition based on hidden Markov models with trajectory of hand motion. Proc. Eng. 15 (2011), 3739--3743.
[16]
F. Lacquaniti and C. Terzuolo. 1983. The law relating the kinematic and figural aspects of drawing movements. Acta Psychol. 54 (1983), 115--130.
[17]
Francesco Lacquaniti, Carlo Terzuolo, and Paolo Viviani. 1983. The law relating the kinematic and figural aspects of drawing movements. Acta Psychol. 54, 13 (1983), 115--130.
[18]
F. Lacquaniti, C. Terzuolo, and P. Viviani. 1984. Global Metric Properties and Preparatory Processes in Drawing Movements. 357--370 pages.
[19]
Donald Marquardt. 1963. An algorithm for least-squares estimation of nonlinear parameters. SIAM J. Appl. Math. 11, 2 (1963), 43--441.
[20]
David Marr and Lucia Vaina. 1982. Representation and recognition of the movements of shapes. Proc. Roy. Soc. Lond. B: Biol. Sci. 214, 1197 (1982), 501--524.
[21]
George Mather, Kirstyn Radford, and Sophie West. 1992. Low-level visual processing of biological motion. Proc. Roy. Soc. Lond. B: Biol. Sci. 249, 1325 (1992), 149--155.
[22]
Giorgio Metta et al. 2010. The iCub humanoid robot: An open-systems platform for research in cognitive development. Neur. Netw. 23, 8 (2010), 1125--1134.
[23]
Rafael Muñoz-Salinas, Eugenio Aguirre, and Miguel García-Silvente. 2007. People detection and tracking using stereo vision and color. Image Vis. Comput. 25, 6 (2007), 995--1007.
[24]
Nicoletta Noceti and Francesca Odone. 2012. Learning common behaviors from large sets of unlabeled temporal series. Image Vis. Comput. 30, 11 (2012), 875--895.
[25]
N. Noceti, A. Sciutti, and G. Sandini. 2015. Cognition helps vision: Recognizing biological motion using invariant dynamic cues. In Proceedings of the International Conference on Image Analysis and Processing (ICIAP’15). 676--686.
[26]
Charalambos Papaxanthis, Christos Paizis, Olivier White, Thierry Pozzo, and Natale Stucchi. 2012. The relation between geometry and time in mental actions. Plos One 7, 11 (2012), e51191.
[27]
Réjean Plamondon and Wacef Guerfali. 1998. The 2/3 power law: When and why? Acta Psychol. 100, 1 (1998), 85--96.
[28]
Cen Rao, Alper Yilmaz, and Mubarak Shah. 2002. View-invariant representation and recognition of actions. Int. J. Comput. Vis. 50, 2 (2002), 203--226.
[29]
Siddharth S. Rautaray and Anupam Agrawal. 2015. Vision based hand gesture recognition for human computer interaction: A survey. Artif. Intell. Rev. 43, 1 (2015), 1--54.
[30]
Zhou Ren, Junsong Yuan, Jingjing Meng, and Zhengyou Zhang. 2013. Robust part-based hand gesture recognition using kinect sensor. IEEE Trans. Multimedia 15, 5 (2013), 1110--1120.
[31]
M. J. E. Richardson and T. Flash. 2002. Comparing smooth arm movements with the two-thirds power law and the related segmented-control hypothesis. J. Neurosci. 22, 18 (2002), 8201--8211.
[32]
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, and Martin Giese. 2005. Learning features of intermediate complexity for the recognition of biological motion. In Proceedings of the Internet Corporation for Assigned Names and Numbers (ICANN’05). Vol. 3696. 241--246.
[33]
Francesca Simion, Lucia Regolin, and Hermann Bulf. 2008. A predisposition for biological motion in the newborn baby. Proc. Natl. Acad. Sci. U.S.A. 105, 2 (2008), 809--813.
[34]
D. Sternad and S. Stefan. 1999. Segmentation of endpoint trajectories does not imply segmented control. Exp. Brain Res. 124, 1 (1999), 118--136.
[35]
T. Tommasi, F. Orabona, and B. Caputo. 2008. Discriminative cue integration for medical image annotation. Pattern Recogn. Lett. 29, 15 (Nov. 2008), 1996--2002.
[36]
Nikolaus F. Troje. 2002. Decomposing biological motion: A framework for analysis and synthesis of human gait patterns. J. Vis. 2, 5 (2002), 2--2.
[37]
Nikolaus F. Troje and Cord Westhoff. 2006. The inversion effect in biological motion perception: Evidence for a “Life Detecto”? Curr. Biol. 16, 8 (2006), 821--824.
[38]
Prahlad Vadakkepat, Peter Lim, Liyanage C. De Silva, Liu Jing, and Li Li Ling. 2008. Multimodal approach to human-face detection and tracking. IEEE Trans. Industr. Electron. 55, 3 (2008), 1385--1393.
[39]
Stphane Vieilledent, Yves Kerlirzin, Stphane Dalbera, and Alain Berthoz. 2001. Relationship between velocity and curvature of a human locomotor trajectory. Neurosci. Lett. 305, 1 (2001), 65--69.
[40]
Alessia Vignolo, Francesco Rea, Nicoletta Noceti, Alessandra Sciutti, Francesca Odone, and Giulio Sandini. 2016. Biological movement detector enhances the attentive skills of humanoid robot iCub. In Humanoids. IEEE, 338--344.
[41]
Paolo Viviani. 1997. The relationship between curvature and velocity in two-dimensional smooth pursuit eye movements. J. Neurosci. 17, 10 (May 1997), 3932--3945.
[42]
P. Viviani, G. Baud-Bovy, and M. Redolfi. 1997. Perceiving and tracking kinesthetic stimuli: Further evidence of motor-perceptual interactions. J. Exp. Psychol. Hum. Percept. Perform. 23, 4 (1997), 1232--1252.
[43]
P. Viviani and M. Cenzato. 1985. Segmentation and coupling in complex movements. J. Exp. Psychol. Hum. Percept. Perform. 11 (1985), 828--845.
[44]
P. Viviani and T. Flash. 1995. Minimum-jerk, two-thirds power law, and isochrony: Converging approaches to movement planning. J. Exp. Psychol. Hum. Percept. Perform. 21, 1 (1995), 32--.
[45]
P. Viviani and G. McCollum. 1983. The relation between linear extent and velocity in drawing movements. Neuroscience 10, 1 (1983), 211--218.
[46]
P. Viviani and R. Schneider. 1991. A developmental study of the relationship between geometry and kinematics in drawing movements. J. Exp. Psychol. Hum. Percept. Perform. 17, 1 (1991), 198--.
[47]
Paolo Viviani and Natale Stucchi. 1989. The effect of movement velocity on form perception: Geometric illusions in dynamic displays. Percept. Psychophys. 46, 3 (1989), 266--274.
[48]
P. Viviani and N. Stucchi. 1992. Biological movements look uniform: Evidence of motor-perceptual interactions. J. Exp. Psychol. Hum. Percept. Perform. 18, 3 (1992), 603--623.
[49]
P. Viviani and C. Terzuolo. 1982. Trajectory determines movement dynamics. Neuroscience 7, 2 (1982), 431--437.
[50]
X. Wang, X. Ma, and W. E. Grimson. 2009. Unsupervised activity perception in crowded and complicated scenes using hierarchical bayesian models. IEEE Trans. Pattern Anal. Mach. Intell. 31, 3 (2009), 539--555.
[51]
Daniel Weinland, Remi Ronfard, and Edmond Boyer. 2011. A survey of vision-based methods for action representation, segmentation and recognition. Comput. Vis. Image Understand. 115, 2 (2011), 224--241.

Cited By

View all

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Applied Perception
ACM Transactions on Applied Perception  Volume 14, Issue 3
July 2017
148 pages
ISSN:1544-3558
EISSN:1544-3965
DOI:10.1145/3066910
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 June 2017
Accepted: 01 March 2017
Revised: 01 February 2017
Received: 01 November 2016
Published in TAP Volume 14, Issue 3

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Biological motion perception
  2. motion perception development
  3. two-thirds power law

Qualifiers

  • Research-article
  • Research
  • Refereed

Funding Sources

  • European CODEFROR project

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)17
  • Downloads (Last 6 weeks)0
Reflects downloads up to 03 Feb 2025

Other Metrics

Citations

Cited By

View all

View Options

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media