Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

Extraction and Analysis of Multiple Periodic Motions in Video Sequences

Published: 01 July 2007 Publication History

Abstract

The analysis of periodic or repetitive motions is useful in many applications, such as the recognition and classification of human and animal activities. Existing methods for the analysis of periodic motions first extract motion trajectories using spatial information and then determine if they are periodic. These approaches are mostly based on feature matching or spatial correlation, which are often infeasible, unreliable, or computationally demanding. In this paper, we present a new approach, based on the time-frequency analysis of the video sequence as a whole. Multiple periodic trajectories are extracted and their periods are estimated simultaneously. The objects that are moving in a periodic manner are extracted using the spatial domain information. Experiments with synthetic and real sequences display the capabilities of this approach.

References

[1]
Y.A. Ivanov and A.F. Bobick, “Recognition of Visual Activities and Interactions by Stochastic Parsing,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 852-872, Aug. 2000.
[2]
M. Brand and V. Kettnaker, “Discovery and Segmentation of Activities in Video,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 844-851, Aug. 2000.
[3]
C. Lu and N. Ferrier, “Repetitive Motion Analysis: Segmentation and Event Classification,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 2, pp. 258-263, Feb. 2004.
[4]
R. Cutler and L.S. Davis, “Robust Real-Time Periodic Motion Detection, Analysis, and Applications,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 781-796, Aug. 2000.
[5]
D. Cremers, S. Osher, and S. Soatto, “Kernel Density Estimation and Intrinsic Alignment for Knowledge-Driven Segmentation: Teaching Level Sets to Walk,” Pattern Recognition, vol. 3175, pp.36-44, Feb. 2004.
[6]
D. Cremers and S. Soatto, “Probabilistic and Sequential Computation of Optical Flow Using Temporal Coherence,” Int'l J. Computer Vision, vol. 62, no. 3, pp. 249-265, May 2005.
[7]
T. Brox, A. Bruhn, N. Papenberg, and J. Weickert, “High Accuracy Optical Flow Estimation Based on a Theory for Warping,” Proc. Eighth European Conf. Computer Vision, vol. 4, pp. 25-36, May 2004.
[8]
S. Seitz and C.R. Dyer, “View-Invariant Analysis of Cyclic Motion,” Int'l J. Computer Vision, vol. 25, no. 3, pp. 231-251, 1997.
[9]
P. Tsai, M. Shah, K. Keiter, and T. Kasparis, “Cyclic Motion Detection for Motion Based Recognition,” Pattern Recognition, vol. 27, no. 12, pp. 1591-1603, 1994.
[10]
F. Liu and R.W. Picard, “Periodicity, Directionality, and Randomness: Wold Features for Image Modeling and Retrieval,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 7, pp.722-733, July 1996.
[11]
R. Polana and R. Nelson, “Detection and Recognition of Periodic, Nonrigid Motion,” Int'l J. Computer Vision, vol. 23, no. 3, pp. 261-282, 1997.
[12]
L. Wang, T. Tan, W. Hu, and H. Ning, “Automatic Gait Recognition Based on Statistical Shape Analysis,” IEEE Trans. Image Processing, vol. 12, no. 9, pp. 1120-1131, Sept. 2003.
[13]
A. Briassouli and N. Ahuja, “Fusion of Frequency and Spatial Domain Information for Motion Analysis,” Proc. 17th Int'l Conf. Pattern Recognition, vol. 2, pp. 175-178, Aug. 2004.
[14]
J.L. Barron, D.J. Fleet, S.S. Beauchemin, and T.A. Burkitt, “Performance of Optical Flow Techniques,” Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 236-242, June 1992.
[15]
J. Domingo, G. Ayala, and E. Dias, “A Method for Multiple Rigid-Object Motion Segmentation Based on Detection and Consistent Matching of Relevant Points in Image Sequences,” Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, vol. 4, pp. 3021-3024, Apr. 1997.
[16]
P. Milanfar, “Two-Dimensional Matched Filtering for Motion Estimation,” IEEE Trans. Image Processing, vol. 8, no. 3, pp. 438-444, Mar. 1999.
[17]
W. Hoge, D. Mitsouras, F. Rybicki, R. Mulkern, and C.-F. Westin, “Registration of Multi-Dimensional Image Data via Sub-Pixel Resolution Phase Correlation,” Proc. IEEE Int'l Conf. Image Processing, pp. 707-710, Sept. 2003.
[18]
R.E. Blahut, Fast Algorithms for Digital Signal Processing. Addison-Wesley, 1984.
[19]
P. Duhamel and M. Vetterli, “Fast Fourier Transforms: A Tutorial Review,” Signal Processing, vol. 19, pp. 259-299, 1990.
[20]
J.S. Walker, Fast Fourier Transform, second ed. CRC Press, 1996.
[21]
R.W. Young and N.G. Kingsbury, “Frequency-Domain Motion Estimation Using a Complex Lapped Transform,” IEEE Trans. Image Processing, vol. 2, no. 1, pp. 2-17, 1993.
[22]
W. Yu, G. Sommer, and K. Daniilidis, “Multiple Motion Analysis: In Spatial or in Spectral Domain?” Computer Vision and Image Understanding, vol. 90, pp. 129-152, 2003.
[23]
W. Chen, G.B. Giannakis, and N. Nandhakumar, “A Harmonic Retrieval Framework for Discontinuous Motion Estimation,” IEEE Trans. Image Processing, vol. 7, no. 9, pp. 1242-1257, Sept. 1998.
[24]
M. Piccardi, “Background Subtraction Techniques: A Review,” Proc. IEEE Conf. Systems, Man, and Cybernetics, pp. 3099-3104, 2004.
[25]
R. Pless, J. Larson, S. Siebers, and B. Westover, “Evaluation of Local Models of Dynamic Backgrounds,” Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 1063-1069, June 2003.
[26]
C. Stauffer and W. Grimson, “Adaptive Background Mixture Models for Real-Time Tracking,” Proc. IEEE Conf. Computer Vision Pattern Recognition, pp. 246-252, June 1999.
[27]
D.H.A. Elgammal and L. Davis, “Nonparametric Model for Background Subtraction,” Proc. European Conf. Computer Vision, pp. 751-767, June 2000.
[28]
L. Cohen, “Time-Frequency Distributions—A Review,” Proc. IEEE, vol. 77, no. 7, pp. 941-981, July 1989.
[29]
A.M. Sayeed and D.L. Jones, “Analysis and Synthesis of Multicomponent Signals Using Positive Time-Frequency Distributions,” IEEE Trans. Signal Processing, vol. 47, no. 2, pp. 493-504, Feb. 1999.
[30]
R. Czerwinski and D. Jones, “Adaptive Short-Time Fourier Analysis,” IEEE Signal Processing Letters, vol. 4, no. 2, pp. 42-45, Feb. 1997.
[31]
A.M. Sayeed and D.L. Jones, “Optimal Quadratic Detection and Estimation Using Generalized Joint Signal Representations,” IEEE Trans. Signal Processing, vol. 44, no. 12, pp. 3031-3043, Dec. 1996.
[32]
A.M. Sayeed and D.L. Jones, “Optimal Kernels for Nonstationary Spectral Estimation,” IEEE Trans. Signal Processing, vol. 43, no. 2, pp. 478-490, Feb. 1995.
[33]
F.J. Harris, “On the Use of Windows for Harmonic Analysis with the Discrete Fourier Transform,” Proc. IEEE, vol. 66, pp. 51-83, 1978.
[34]
P. Kootsookos, B. Lovell, and B. Boashash, “A Unified Approach to the STFT, TFDs and Instantaneous Frequency,” IEEE Trans. Signal Processing, vol. 40, no. 8, pp. 1971-1982, 1992.
[35]
I. Djurovic and S. Stankovic, “Estimation of Time-Varying Velocities of Moving Objects by Time-Frequency Representations,” IEEE Trans. Signal Processing, vol. 47, no. 2, pp. 493-504, Feb. 1999.
[36]
S. Stankovic and I. Djurovic, “Motion Parameter Estimation by Using Time-Frequency Representations,” Electronics Letters, vol. 37, no. 24, pp. 1446-1448, Nov. 2001.
[37]
P. Kornprobst, R. Deriche, and G. Aubert, “Nonlinear Operators in Image Restoration,” Proc. Int'l Conf. Computer Vision and Pattern Recognition, pp. 325-331, June 1997.
[38]
A. Hirani and T. Totsuka, “Combining Frequency and Spatial Domain Information for Fast Interactive Image Noise Removal,” Proc. ACM SIGGRAPH, pp. 269-276, 1996.
[39]
B. Barkat and K. Abed-Meraim, “A Blind Components Separation Procedure for FM Signal Analysis,” Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, vol. 2, pp. 1425-1428, June 2002.
[40]
S.M. Kay, Modern Spectral Estimation, Theory and Applications. Prentice-Hall, 1988.
[41]
A. Papoulis, Probability, Random Variables, and Stochastic Processes, second ed. McGraw-Hill, 1987.
[42]
D. Jones and T. Parks, “A Resolution Comparison of Several Time-Frequency Representations,” IEEE Trans. Signal Processing, vol. 40, no. 2, pp. 413-420, Feb. 1992.

Cited By

View all

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence  Volume 29, Issue 7
July 2007
193 pages

Publisher

IEEE Computer Society

United States

Publication History

Published: 01 July 2007

Author Tags

  1. Periodic motion analysis
  2. short term Fourier transform.
  3. time-frequency distributions

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 22 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2023)High‐precision skeleton‐based human repetitive action countingIET Computer Vision10.1049/cvi2.1219317:6(700-709)Online publication date: 28-Mar-2023
  • (2023)Full Resolution Repetition CountingIntelligent Robotics and Applications10.1007/978-981-99-6483-3_48(563-574)Online publication date: 5-Jul-2023
  • (2019)On Visual Periodicity Estimation Using Singular Value DecompositionJournal of Mathematical Imaging and Vision10.1007/s10851-019-00894-z61:8(1135-1153)Online publication date: 1-Oct-2019
  • (2016)Real-time counting of moving objects in complex environmentsProceedings of the 31st Annual ACM Symposium on Applied Computing10.1145/2851613.2851714(588-595)Online publication date: 4-Apr-2016
  • (2013)Computational behaviour modelling for autism diagnosisProceedings of the 15th ACM on International conference on multimodal interaction10.1145/2522848.2532191(361-364)Online publication date: 9-Dec-2013
  • (2010)A low false negative filter for detecting rare bird species from short video segments using a probable observation data set-based EKF methodIEEE Transactions on Image Processing10.1109/TIP.2010.204815119:9(2321-2331)Online publication date: 1-Sep-2010
  • (2010)3D Reconstruction of Periodic Motion from a Single ViewInternational Journal of Computer Vision10.1007/s11263-010-0334-x90:1(28-44)Online publication date: 1-Oct-2010
  • (2009)State-of-the-art on spatio-temporal information-based video retrievalPattern Recognition10.1016/j.patcog.2008.08.03342:2(267-282)Online publication date: 1-Feb-2009

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media