Without knowledge of background or motion feature, detecting humans from a 2D image is still a tough task. In this paper, a novel stereo-based method to detect human objects for mobile service robots is proposed. Human objects are detected from the stereo spatial space through three distinct steps: (i) human oriented scale-adaptive filtering to aggregate and enhance the evidence of human presence, (ii) human like object segmentation, and (iii) human object identification based on the matching of a deformable head shoulder template to the evidence from both stereo and edge information. Systematic evaluation of the experimental results show that the high accuracy rates for human detection have been achieved with fewer constraints on the human operator, robot and the environment which they are in.