Crowd animation is a topic of high interest which offers many challenges. One of the most important is the trade-off between rich, realistic behaviors, and computational costs. To this end, much effort has been put into creating variety in character representation and animation. Nevertheless, one aspect still lacking realism in virtual crowd characters resides in their attention behaviors. In this paper, we propose a framework to add gaze attention behaviors to crowd animations. First, We automatically extract interest points from character or object trajectories in pre-existing animations. For a given character, We assign a set of elementary scores based on parameters such as distance or speed to all other characters or objects in the scene. We then combine these subscores in all overall scoring function. The scores obtained from this function form a set of gaze constraints that determine where and when each character should look. We finally enforce these constraints With all optimized dedicated gaze Inverse Kinematics (IK) solver. It first computes Me displacement maps for the constraints to be satisfied. It then smoothly propagates these displacements over all automatically defined number of frames. We demonstrate the efficiency of our method and our visually convincing results through various examples. Copyright (C) 2009 John Wiley & Sons, Ltd.