Human/biological motion analysis is traditionally addressed as a problem of tracking a set of (active/passive) markers appropriately attached to the body part under study. General, fundamentally three-dimensional movements cannot be studied in this way. After having studied for some time the different aspects of such a subtly complex research topic,1,2 we propose now an approach which is model- driven, in the sense that it is based on an Animated Humanoid and on the comparison between the actual images of the body and the synthetic images of the humanoid. Our system (that we dubbed Kinesis) organizes the computation into three main phases: (1) Image (sequence) acquisition and processing, (2) Humanoid animation, (3) Optimization. Images acquisition and processing is performed on a VDS Eidobrain video- workstation, which allows image sequences to be stored from three video inputs. The second module relies on a distributed model of motor control, which solves motor redundancy through the regularizing properties of muscle elasticity.3,4 The optimization module drives the humanoid animation in such a way to find the best fit between the original data and the humanoid. Kinesis requires two calibration: the photogrammetric calibration of the (at least three) cameras and calibration of the humanoid. Preliminary results are presented.