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2 results

  • 9 - Image Data

  • from Part II - Case Studies
  • Pablo Duboue
  • Book:
    The Art of Feature Engineering
    Published online:
    29 May 2020
    Print publication:
    25 June 2020, pp 212-232

  • Summary

    The last chapter using the dataset from chapter 6, this time the dataset is expanded using 80 thousand satellite images obtained from NASA for relative humidity density as it relates to vegetation. This image information is not visible information and thus pre-trained models are not useful for this problem. Instead, traditional computer vision techniques are showcased, involving histograms, local feature extraction, gradients and histograms of gradients. This domain exemplifies how to deal with high level of nuisance noise, how to normalize your features so that a small changes in the way the information was acquired does not completely throws off the underlining machine learning mechanism. These takeaways are valuable for anybody working with sensor data where the acquisition process has a high level of uncertainty. The domain also exemplifies working with large number of low-level sensor data.

  • Real-time object tracking from corners

  • Han Wang, Choon Seng Chua, Ching Tong Sim
  • Journal:
    Robotica / Volume 16 / Issue 1 / January 1998
    Published online by Cambridge University Press:
    01 January 1998, pp. 109-116

  • This paper reports a visual tracking system that can track moving objects in real-time with a modest workstation equipped with a pan-tilt device. The algorithm essentially has three parts: (1) feature detection, (2) tracking and (3) control of the robot head. Corners are viewpoint invariant, hence being utilised as the beacon for tracking. Tracking is performed in two stages of Kalman filtering and affine transformation. A technique of reducing greatly the computational time for the correlaton is also described. The Kalman filter predicts intelligently the fovea window and reduced computation dramatically. The affine transformation deals with the unexpected events when there is partial occlusion.