(for the bottom). Then, we calculated two character-
istic vectors and combined them to get one vector de-
scriptor. Each human silhouette extracted is converted
to a common space 128 x 48 to get the invariance to
translation and scale. For rotation invariance, we sup-
posed that the vertical is preserved.

Figure 4: Krawtchouk polynomial for up and bottom

According to some related works, we chose to calcu-
late Krawtchouk moment with parameter (m = n). In
order to ﬁnd the best value of n, we used a database
with 600 simulated silhouettes and done cross valida-
tion over all. The ﬁg 5 show that from order (n = m =
24), we got a stable and best accuracy for pose recog-
nition. So, the ﬁnal feature vector has 48 dimensions.
VISAPP_HumanPoseEstimation