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Two problems from a university-level statistics course focused on image and video processing. The first problem deals with evaluating the probability of observing a sequence of symbols given a hidden markov model. The second problem involves a simplified graphical model for hand silhouettes, where the orientation and angles of the fingers are modeled as random variables. Hints and suggests writing a computer program to evaluate the expected value of the angle of the third finger.
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Problem 1 (Hidden Markov Model). Consider the following HMM. The hidden sequence S 0 , S 1 , S 2 , S 3 is a homogeneous Markov chain with alphabet Λ = { 0 , 1 } and transition prob-
ability matrix Q =
. The observed variables are X = {X 0 , · · · , X 7 } ∈ Λ^8. The
conditional pmf for X given S is given by
p(x|s) =
i=
Q(x 2 i|si)Q(x 2 i+1|si).
Give a computationally efficient algorithm for evaluating p(x 7 |s 0 ).
Problem 2 (Simplified graphical model for hand silhouettes). Say the global orientation of the hand is represented by a variable O, all fingers have prespecified lengths, and the angle subtended by fingers 1 and 5 (the pinkie and the thumb) is denoted by A. The orientation of the five fingers is represented by angular variables F 1 , · · · , F 5. In this simplified model, the hand is parameterized by the 7 variables F 1 , · · · , F 5 , O, A.
These variables are modeled as random with the following joint pdf:
p(f 1 , · · · , f 5 , o, a) =
ψ 15 (f 1 , f 5 |o, a)ψ 12 (f 1 , f 2 )ψ 23 (f 2 , f 3 )ψ 34 (f 3 , f 4 )ψ 45 (f 4 , f 5 )p(o)p(a).
ψi,i+1(fi, fi+1) = exp{fi − fi+1} (^1) {fi<fi+1} : i = 1, 2 , 3
= exp{
(fi − fi+1)} (^1) {fi<fi+1} : i = 4
ψ 15 (f 1 , f 5 |o∗, 10) = exp{ 106 |f 1 + 5| + 10^6 |f 5 − 5 |}.
Write a computer program and evaluate the expected value of F 3. Hint: you should be able to make a rough guess of that value before writing the program.