understanding "hypersphere"/"high density region" from paper

[no-zzz-un]

Beyond that, assuming that an autoencoder is correctly learned respecting the latent space Gaussianity, we can generate realistic looking videos as long as the transition model never leaves the high density region of the embedding space. This high density region is a hypersphere of radius ⇢, which in its turn is function of the dimensionality of embedding space and variance of Gaussian prior.

that makes it sound like all latent space encodings which "look realistic" when decoded by the generator have equal distance from some centroid. am i misunderstanding something here? isn't it trivial to stay in the "high density region" in that case?