Inferring dynamic behavior of the heart from its image sequences is a very important research area in biomedical engineering. It provides an invaluable tool for noninvasive evaluation of myocardial functions. This paper presents estimation algorithms for the analysis of heart motion and deformation over a cardiac cycle, as well as the visualization techniques for the animation of moving heart evolution. The first part of the paper is devoted to the analysis of the heart motion and deformation. The research is based on the general belief that the human heart undergoes both global motion and local deformation, and is conducted on the angiographic data of the heart. The authors identify the global motion as the relative position and orientation change of the heart as a whole and estimate the motion parameters from the 3- D data of the bifurcation points. They also develop a recursive algorithm for estimating global motion and object shape in order to combat the biased distribution of the bifurcation points. Upon compensation for the global motion, a tensor analysis based approach is introduced to parameterize the deformation of localized region. The estimated stretch tensors give the directions and magnitudes of extreme deformation for each localized region. In the second part of the paper, several visualization techniques are presented to vividly examine the spatial and time varying nature of the heart. Animations of global motion compensation and local deformation evolution are generated using the original data and estimation results. Display showing the heart in slow motion is created by interpolating original and estimated data between image frames. Visualization operations such as camera and lighting manipulation, polygon outlining, color coding, and so on are applied to the data to reveal the complex nature of the beating heart.