Automatic recovery of eye gestures from image sequences is one of the important topics for face recognition and model-based coding of videophone sequences. Usually complicated models of the eye and its motion are used. In this contribution, eye gesture parameter estimation is described. A previously published automatic eye detection/tracking algorithm, based on template matching, is used for the eye pose detection. The eye gesture analysis is realized with a mathematical morphology scale-space approach, forming spatio-temporal curves out of scale measurement statistics. The resulting curves provide a direct measure of the eye gesture, which can then be used as an eye animation parameter. Experimental results demonstrate the efficiency and robustness.