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Dynamic Two Level Threshold Estimation for Zero Motion Prejudgment: A Step Towards Fast Motion Estimation

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Advances in Computing and Data Sciences (ICACDS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 721))

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Abstract

In most video sequences, especially containing slow motion, a large number of blocks are stationary. Early determination of these blocks may save large number of computations in any motion estimation (ME) algorithm. The decision for declaring a block to be stationary can be made by comparing the block distortion with a predetermined threshold whose large or small values may affect the speed and accuracy of a ME algorithm. Accurate prediction of this threshold proposes a challenging problem. In this manuscript, a dynamic two level threshold estimation technique has been proposed. This two level scheme not only detects constant variations in the neighboring blocks but is also capable of detecting stationary blocks with abrupt variations. Performance of the proposed technique is evaluated by implementing ZMP before ME process in adaptive rood pattern search (ARPS) algorithm. Simulation results show better performance of proposed technique in comparison to single level dynamic threshold predictor and fixed threshold predictor.

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Authors and Affiliations

  1. MSIT, Janakpuri, New Delhi, India

    Shaifali M. Arora

  2. The NorthCap University, Gurugram, Haryana, India

    Kavita Khanna

Authors
  1. Shaifali M. Arora
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  2. Kavita Khanna
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Corresponding author

Correspondence to Kavita Khanna .

Editor information

Editors and Affiliations

  1. Krishna Engineering College, Ghaziabad, Uttar Pradesh, India

    Mayank Singh

  2. Jaypee University of Information Technology, Waknaghat, Himachal Pradesh, India

    P.K. Gupta

  3. Department of Computer Science and Engineering, Raghogarh, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. Indira Gandhi Delhi Technical University, New Delhi, India

    Arun Sharma

  5. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Ontario, Canada

    Tuncer Ören

  6. Department of Computer and Information Science, University of Michigan-Dearborn, Dearborn, Michigan, USA

    William Grosky

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© 2017 Springer Nature Singapore Pte Ltd.

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Arora, S.M., Khanna, K. (2017). Dynamic Two Level Threshold Estimation for Zero Motion Prejudgment: A Step Towards Fast Motion Estimation. In: Singh, M., Gupta, P., Tyagi, V., Sharma, A., Ören, T., Grosky, W. (eds) Advances in Computing and Data Sciences. ICACDS 2016. Communications in Computer and Information Science, vol 721. Springer, Singapore. https://doi.org/10.1007/978-981-10-5427-3_29

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  • DOI: https://doi.org/10.1007/978-981-10-5427-3_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5426-6

  • Online ISBN: 978-981-10-5427-3

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