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Automatic moving object detection/extraction has been explored extensively by the computer vision community. Unfortunately majority of the work has been limited to stationary cameras, in which background subtraction is utilized as the major methodology. In this paper, we will present a technique to tackle the problem in the case of moving camera which is the most often encountered situation in real life for target tracking, surveillance, etc. Instead of focusing on two adjacent time frames, our object detection rests on three consecutive video frames, a backward frame, the frame of interest and a forward frame. Firstly, optical flow based simultaneous iterative camera motion compensation and background estimation is carried out on backward and forward frames. Differences between camera motion compensated backward and forward frames with the frame of interest are then tested against the estimated background models for intensity change detection. Next, these change detection results are combined together for acquiring approximate shape of the moving object. Experimental results for a video sequence with moving camera are presented.