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Lucas-Kanade 20 Years On: A Unifying Framework: Part 2
S. Baker, R. Gross, I. Matthews, and T. Ishikawa
tech. report CMU-RI-TR-03-01, Robotics Institute, Carnegie Mellon University, February, 2003.

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Since the Lucas-Kanade algorithm was proposed in 1981, image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms have been proposed and a wide variety of extensions have been made to the original formulation. We present an overview of image alignment, describing most of the algorithms and their extensions in a consistent framework. We concentrate on the inverse compositional algorithm, an efficient algorithm that we recently proposed. We examine which of the extensions to the Lucas-Kanade algorithm can be used with the inverse compositional algorithm without any significant loss of efficiency, and which require extra computation. In this paper, Part 2 in a series of papers, we cover the choice of the error function. We first consider weighted L2 norms. Afterwards we consider robust error functions.

Sponsor: US Department of Defense
Grant ID: N41756-03-C4024

Associated center: VASC
Associated labs/groups: Vision for Safe Driving, People Image Analysis Consortium, and Face Group
Associated projects: AAMs with Occlusion, AAM Fitting Algorithms, Lucas-Kanade 20 Years On, Face Model Building and Fitting, Face and Facial Feature Tracking, and Car Tracking

S. Baker, R. Gross, I. Matthews, and T. Ishikawa, Lucas-Kanade 20 Years On: A Unifying Framework: Part 2, tech. report CMU-RI-TR-03-01, Robotics Institute, Carnegie Mellon University, February, 2003.

@techreport{Baker_2003_4302,
   author = "Simon Baker and Ralph Gross and Iain Matthews and Takahiro Ishikawa",
   title = "Lucas-Kanade 20 Years On: A Unifying Framework: Part 2",
   institution = "Robotics Institute, Carnegie Mellon University",
   month = "February",
   year = "2003",
   number = "CMU-RI-TR-03-01",
   address = "Pittsburgh, PA"
}