In this paper, we propose a method for detecting moving objects in a video stream. Initially four existing methods, Basic Background Subtraction (BSS), Frame Differencing (FD), Adaptive Background Subtraction (ABS) and Background Subtraction Frame Differencing (BSFD) are evaluated for low resolution action recognition videos. Focus of this paper is on low resolution videos as most of the time CCTV recordings of the public areas are of low resolution. Recognizing an action performed by a human being in such a video is a challenging task. Videos recorded with various view angles are used for testing to evaluate view invariance property of algorithms. Concept of three frame differencing method is used along with adaptive background in an Adaptive Background subtraction and Frame Differencing (ABSFD) method proposed in this paper. A dynamic background image is used to detect the moving object. Background is updated with small constant value to accommodate minute changes in background. The proposed algorithm gives consistent results for videos recorded at different view angles. The experimental results show that this algorithm can detect moving objects successfully with precision above 95% in most of the test cases. © 2016 Institution of Engineering and Technology. All rights reserved.