Computer vision for active and assisted living

Computer vision for active and assisted living

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In this chapter, author is going to review how cameras are employed in AAL and what the current state of the art is related to applications and recognition techniques. Author will distinguish between traditional RGB cameras and depth sensors (or multimodal approaches, where both techniques are combined), whose recent great impact in the field deserves an individual overview. With the goal of introducing professionals of other AAL fields to computer vision in general and specifically to its application to assisted living, we will review the image processing pipeline, from different camera types that can be installed in care centres and people's homes to recent advances in image and video feature extraction and classification. For depth sensors, specific applications, feature estimation techniques and the most successful data representations are reviewed to detail how these differentiate from the traditional RGB approaches.

Chapter Contents:

  • 4.1 Introduction
  • 4.2 Using RGB cameras
  • 4.2.1 Applications
  • 4.2.2 Image processing stages
  • Image acquisition
  • Image pre-processing
  • Feature extraction and recognition
  • 4.3 Using depth sensors
  • 4.3.1 Skeletal
  • 4.3.2 Depth maps
  • 4.3.3 Point clouds
  • 4.3.4 Plan-view maps
  • 4.3.5 Accuracy
  • 4.4 Conclusion
  • References

Inspec keywords: computer vision; health care; feature extraction; cameras; assisted living; video signal processing; image colour analysis; image recognition; image classification

Other keywords: video feature extraction; image processing pipeline; depth sensors; image feature extraction; assisted living; image feature classification; people homes; video feature classification; feature estimation; RGB cameras; AAL; active living; computer vision; care centres

Subjects: Computer vision and image processing techniques; Image recognition; Video signal processing; Biology and medical computing; Home computing

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