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RGB-Depth Image Based Human Detection Using Viola-Jones and Chan-Vese Active Contour Segmentation

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Advances in Signal Processing and Intelligent Recognition Systems (SIRS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 678))

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Abstract

Human detection refers to the process of detecting human region from an image or from video frames. Most of the recent advanced human detection systems use the segmentation scheme by incorporating the depth information of the scene. In such systems, the scene gets captured by a RGB-D camera and the candidate area is segmented by setting an appropriate depth threshold for the captured depth images. In practice, depth data obtained from this depth analysis having critical problems, such as optical noise, absence of depth information for certain regions like hair area, and unmatched boundaries. The proposed approach mainly focus on restoring the actual edge information and hair area of the subject in the pre-segmented image by applying Viola Jones Algorithm for face area detection and Chan-Vese active contour detection for restoring hair and edge areas of the image over the detected face area. This final segmentation mask is used for segmenting the accurate human region from the original image with hair area and with boundaries similar to the ground truth. Experimental results prove the improvement in the visual quality of the segmented human area.

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Authors and Affiliations

  1. Institut Für Medientechnic, Technische Universität Ilmenau, Ilmenau, Germany

    Puji Lestari & Hans-Peter Schade

  2. Research Center for Informatics, Indonesian Institute of Sciences, Jakarta, Indonesia

    Puji Lestari

Authors
  1. Puji Lestari
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  2. Hans-Peter Schade
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Correspondence to Puji Lestari .

Editor information

Editors and Affiliations

  1. School of CS/IT, Indian Institute of Information Technology and Management, Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada

    Sri Krishnan

  3. Department of Computer Science, University of Salamanca, Salamanca, Salamanca, Spain

    Juan Manuel Corchado Rodriguez

  4. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

  5. Department of Systems and Computer Networks, Wroclaw University of Science and Technology, Wroclaw, Poland

    Michal Wozniak

  6. Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, United Kingdom

    Dhiya Al-Jumeily

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Lestari, P., Schade, HP. (2018). RGB-Depth Image Based Human Detection Using Viola-Jones and Chan-Vese Active Contour Segmentation. In: Thampi, S., Krishnan, S., Corchado Rodriguez, J., Das, S., Wozniak, M., Al-Jumeily, D. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2017. Advances in Intelligent Systems and Computing, vol 678. Springer, Cham. https://doi.org/10.1007/978-3-319-67934-1_25

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  • DOI: https://doi.org/10.1007/978-3-319-67934-1_25

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