In a conventional hybrid video coding scheme, the choice of encoding parameters (motion vectors, quantization
parameters, etc.) is carried out by optimizing frame by frame the output distortion for a given rate budget.
While it is well known that motion estimation naturally induces a chain of dependencies among pixels, this is
usually not explicitly exploited in the coding process in order to improve overall coding efficiency. Specifically,
when considering a group of pictures with an IPPP... structure, each pixel of the first frame can be thought
of as the root of a tree whose children are the pixels of the subsequent frames predicted by it. In this work,
we demonstrate the advantages of such a representation by showing that, in some situations, the best motion
vector is not the one that minimizes the energy of the prediction residual, but the one that produces a better
tree structure, e.g., one that can be globally more favorable from a rate-distortion perspective. In this new
structure, pixel with a larger descendance are allocated extra rate to produce higher quality predictors. As a
proof of concept, we verify this assertion by assigning the quantization parameter in a video sequence in such a
way that pixels with a larger number of descendants are coded with a higher quality. In this way we are able
to improve RD performance by nearly 1 dB. Our preliminary results suggest that a deeper understanding of the
temporal dependencies can potentially lead to substantial gains in coding performance.