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Using Lucas-Kanade Algorithms to Measure Human Movement

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Information, Communication and Computing Technology (ICICCT 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 835))

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Abstract

As an important part of clinical studies, Motion estimation knowledge is widely used to gather useful movement information for medical professionals to find out the best treatment for chronic pain. The purpose of this project is to develop a program to analyze patients’ movements and therefore to improve the treatment of patients. Initially, the basic Luca-Kanade algorithm was implemented. And this program was primarily improved upon by setting a threshold to decrease the noise, and then by selecting feature points to process. Additionally, the resizing method was adopted to further improve the whole system. The solution successfully meets the project aims as the system performs much better than the original one with higher accuracy and speed, while the motion trail can be represented clearly by multiple optical flow fields and the useful information can be detected from the video through all the improved implementations.

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References

  • Alex, D.S., Wahi, A.: BSFD Background subtraction frame difference algorithm for moving object detection and extraction. J. Theor. Appl. Inf. Technol. 60(3), 623–628 (2014)

    Google Scholar 

  • Baker, S., Matthews, I.: Lucas-Kanade 20 years on: a unifying framework. Int. J. Comput. Vis. 56(3), 221–255 (2004)

    Article  Google Scholar 

  • Bruhn, A., Weickert, J., Schnörr, C.: Lucas/Kanade meets horn/Schunck: combining local and global optic flow methods. Int. J. Comput. Vis. 61(3), 1–21 (2005)

    Article  Google Scholar 

  • Cao, L., Ramesh, B.: Agile requirements engineering practices: an empirical study. IEEE Softw. 25(1), 60–67 (2008)

    Article  Google Scholar 

  • Ding, L., Goshtasby, A.: On the canny edge detector. Pattern Recogn. 34(3), 721–725 (2001)

    Article  Google Scholar 

  • Fortun, D., Bouthemy, P., Kervrann, C.: Optical flow modelling and computation: a survey. Comput. Vis. Image Underst. 134, 1–21 (2015)

    Article  Google Scholar 

  • Gibson, J.J.: The visual perception of objective motion and subjective movement. Psychol. Rev. 101(2), 318–323 (1994)

    Article  Google Scholar 

  • Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital image processing using MATLAB. Dorling Kindersley Pvt, India (2006)

    Google Scholar 

  • Heath, M., Sarkar, S., Sanocki, T., Bowyer, K.: Comparison of edge detectors. Comput. Vis. Image Underst. 69(1), 38–54 (1998)

    Article  Google Scholar 

  • Huang, J.-C., Hsieh, W.-S.: Automatic feature-based global motion estimation in video sequences. IEEE Trans. Consum. Electron. 50(3), 911–915 (2004)

    Article  Google Scholar 

  • Huang, T.-C., Chang, C.-K., Liao, C.-H., Ho, Y.J.: Quantification of blood flow in internal cerebral artery by optical flow method on digital subtraction angiography in comparison with time-of flight magnetic resonance angiography. PLoS ONE 8(1), e54678 (2013)

    Article  Google Scholar 

  • Irani, M., Anandan, P.: About direct methods. In: Triggs, B., Zisserman, A., Szeliski, R. (eds.) IWVA 1999. LNCS, vol. 1883, pp. 267–277. Springer, Heidelberg (2000). https://doi.org/10.1007/3-540-44480-7_18

    Chapter  Google Scholar 

  • Iwata, K., Kikuta, H.: Measurement of dynamic flow field by optical computed tomography with shearing interferometers. Opt. Rev. 7(5), 415–419 (2000)

    Article  Google Scholar 

  • Ko, B., Kim, S., Nam, J.: Image resizing using saliency strength map and seam carving for white blood cell analysis. Biomed. Eng. Online 9(1), 54 (2010)

    Article  Google Scholar 

  • Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: IJCAI, pp. 674–679 (1981)

    Google Scholar 

  • Lu, J., Liou, M.L.: A simple and efficient search algorithm for block-matching motion estimation. IEEE Trans. Circ. Syst. Video Technol. 7(2), 429–433 (1997)

    Article  Google Scholar 

  • Moeslund, T.B., Hilton, A., KrĂĽger, V.: A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Underst. 104(2–3), 90–126 (2006)

    Article  Google Scholar 

  • Nguyen, V.A., Tan, Y.: Fast block-based motion estimation using integral frames. IEEE Signal Process. Lett. 11(9), 744–747 (2004)

    Article  Google Scholar 

  • Niu, Y., Xu, Z., Che, X.: Dynamically removing false features in pyramidal Lucas-Kanade registration. IEEE Trans. Image Process. 23(8), 3535–3544 (2014)

    Article  MathSciNet  Google Scholar 

  • Torr, P.H.S., Zisserman, A.: Feature based methods for structure and motion estimation. In: Triggs, B., Zisserman, A., Szeliski, R. (eds.) IWVA 1999. LNCS, vol. 1883, pp. 278–294. Springer, Heidelberg (2000). https://doi.org/10.1007/3-540-44480-7_19

    Chapter  Google Scholar 

  • Singla, N.: Motion detection based on frame difference method. Int. J. Inf. Comput. Technol. 4(0974–2239), 1559–1565 (2014)

    Google Scholar 

  • Wang, Z., Ben Salah, M., Zhang, H.: Object joint detection and tracking using adaptive multiple motion models. Vis. Comput. 30(2), 173–187 (2013)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Chengdu Neusoft University, Chengdu, China

    Yao Mi

  2. Wuhan University of Technology, Wuhan, China

    Prakash Kumar Bipin

  3. University of Electronic Science and Technology of China, Chengdu, China

    Rajeev Kumar Shah

Authors
  1. Yao Mi
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  2. Prakash Kumar Bipin
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  3. Rajeev Kumar Shah
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Corresponding author

Correspondence to Rajeev Kumar Shah .

Editor information

Editors and Affiliations

  1. School of Computer and Systems Science, Jawaharlal Nehru University, New Delhi, India

    Sonajharia Minz

  2. Indian Institute of Technology Guwahati, Guwahati, India

    Sushanta Karmakar

  3. Jagan Institute of Management Studies, Delhi, India

    Latika Kharb

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Mi, Y., Bipin, P.K., Shah, R.K. (2019). Using Lucas-Kanade Algorithms to Measure Human Movement. In: Minz, S., Karmakar, S., Kharb, L. (eds) Information, Communication and Computing Technology. ICICCT 2018. Communications in Computer and Information Science, vol 835. Springer, Singapore. https://doi.org/10.1007/978-981-13-5992-7_10

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  • DOI: https://doi.org/10.1007/978-981-13-5992-7_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5991-0

  • Online ISBN: 978-981-13-5992-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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