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1.2 A brief history 13

(a) (b) (c)

(d) (e) (f)

Figure 1.8 Examples of computer vision algorithms from the 1980s: (a) pyramid blending (Burt and Adelson
1983b) c 1983 ACM, (b) shape from shading (Freeman and Adelson 1991) c 1991 IEEE, (c) edge detection
(Freeman and Adelson 1991) c 1991 IEEE, (d) physically based models (Terzopoulos and Witkin 1988) c 1988
IEEE, (e) regularization-based surface reconstruction (Terzopoulos 1988) c 1988 IEEE, (f) range data acquisition
and merging (Banno, Masuda, Oishi et al. 2008) c 2008 Springer.

Research into better edge and contour detection (Figure 1.8c) (see Section 4.2) was also
active during this period (Canny 1986; Nalwa and Binford 1986), including the introduc-
tion of dynamically evolving contour trackers (Section 5.1.1) such as snakes (Kass, Witkin,
and Terzopoulos 1988), as well as three-dimensional physically based models (Figure 1.8d)
(Terzopoulos, Witkin, and Kass 1987; Kass, Witkin, and Terzopoulos 1988; Terzopoulos and
Fleischer 1988; Terzopoulos, Witkin, and Kass 1988).
Researchers noticed that a lot of the stereo, flow, shape-from-X, and edge detection al-
gorithms could be unified, or at least described, using the same mathematical framework if
they were posed as variational optimization problems (see Section 3.7) and made more ro-
bust (well-posed) using regularization (Figure 1.8e) (see Section 3.7.1 and Terzopoulos 1983;
Poggio, Torre, and Koch 1985; Terzopoulos 1986b; Blake and Zisserman 1987; Bertero, Pog-
gio, and Torre 1988; Terzopoulos 1988). Around the same time, Geman and Geman (1984)
pointed out that such problems could equally well be formulated using discrete Markov Ran-
dom Field (MRF) models (see Section 3.7.2), which enabled the use of better (global) search
and optimization algorithms, such as simulated annealing.
Online variants of MRF algorithms that modeled and updated uncertainties using the
Kalman filter were introduced a little later (Dickmanns and Graefe 1988; Matthies, Kanade,
and Szeliski 1989; Szeliski 1989). Attempts were also made to map both regularized and
MRF algorithms onto parallel hardware (Poggio and Koch 1985; Poggio, Little, Gamble
et al. 1988; Fischler, Firschein, Barnard et al. 1989). The book by Fischler and Firschein
(1987) contains a nice collection of articles focusing on all of these topics (stereo, flow,