This paper presents a novice method for human and car identification in H.264/AVC compressed video domain. By analyzing the shape and motion vector homogeneity of the segmented objects, we can identify car and human. Our system consists of three main processes: (1) Moving object segmentation based on clustering MVs and Markov Random Field (MRF) iteration, (2) Feature Extraction based on motion analysis to obtain the difference of MVs direction (dMVD) and shape analysis to find the number of MBs (nMB) of an object, and (3) Object classification using Bayesian Classifier. In the experiments, we show that the recognition rate of car and human are 88% and 98% respectively.