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Objects Detection and Tracking Strategies

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Sensors and Image Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 651))

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Abstract

Object detection and tracking play a vital role in several applications like face detection, gait detection, vehicle detection and pose detection, and object recognition. The first step in the object detection algorithm is detecting the presence of any object in video images. The process of the object detection is accomplished using Hidden Markov Models, Support Vector Machines, Machine Learning Techniques, Pattern Recognition, Statistical Method, Scale Invariant Feature, structured visual dictionary (SVD), AdaBoost, Clustering Method, Bayesian Framework, Particle Filtering, Vector Quantization, and Feature Extraction, etc. This paper presents a comprehensive study and analysis on object detection and tracking techniques.

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Authors and Affiliations

  1. Department of Computer Science, Pondicherry University, Pondicherry, India

    Sureshbabu Matla & Ravi Subban

Authors
  1. Sureshbabu Matla
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  2. Ravi Subban
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Corresponding author

Correspondence to Sureshbabu Matla .

Editor information

Editors and Affiliations

  1. Gautam Buddha University, Greater Noida, Uttar Pradesh, India

    Shabana Urooj

  2. Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, Punjab, India

    Jitendra Virmani

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© 2018 Springer Nature Singapore Pte Ltd.

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Matla, S., Subban, R. (2018). Objects Detection and Tracking Strategies. In: Urooj, S., Virmani, J. (eds) Sensors and Image Processing. Advances in Intelligent Systems and Computing, vol 651. Springer, Singapore. https://doi.org/10.1007/978-981-10-6614-6_17

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  • DOI: https://doi.org/10.1007/978-981-10-6614-6_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6613-9

  • Online ISBN: 978-981-10-6614-6

  • eBook Packages: EngineeringEngineering (R0)

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