In this paper we present an environment for the tracking of a human face
obtained from a real video sequence. We will describe the system and discuss
the advantages and disadvantages of our approximation. We mainly focus on
the situation of the main attributes of the human face (eyes, eyebrows, nose and
moth). The tracking algorithm and the ulterior animation of the synthetic model
must guarantee the real time response without the need of any additional
markup of the actor. Due to the complexity of the process, we make an initial
selection of the facial attributes involved without any efficiency or robustness
loss. We define a probabilistic model of skin face area and we would like to
track this region in the sequence of images. In parallel we propose additional
criteria to search inside this tracked area main features in human face (as lisp,
eyes, eyebrows, nose, etc..). The tracking algorithm is based in a efficient
implementation of continuously adaptive mean shift procedure (CAMSHIFT)
and this process is improved also with the second step with feature detections.
In this paper only we present the whole process, the tracking background
criteria and lips detection procedure. The synthesis phase is out scope of this
paper and we generate the facial animations parameters (FAP) as input to a
compliant MPEG-4 facial animation engine (FAE). This system is designed as a
computer interface for controlling commercial computer applications which
include avatar or clones in real time.