Detection of moving objects is one of the key steps for vision based applications. Many previous works leverage background subtraction using background models and assume that image sequences are captured from a stationary camera. These methods are not directly applied to image sequences from a moving camera because both foreground and background objects move with respect to the camera. One of the approaches to tackle this problem is to estimate background movement by computing pixel correspondences between frames such as homography. With this approach, moving objects can be detected by using existing background subtraction. In this paper, we evaluate detection of foreground objects for image sequences from a moving camera. Especially, we focus on homography as a camera motion. In our evaluation we change the following parameters: changing feature points, the number of them and estimation methods of homography. We analyze its effect on detection of moving objects in regard to detection accuracy, processing time. Through experiments, we show requirement of background models in image sequences form a moving camera.