Moving object detection is essential for real-time surveillance; however, it is challenging to support moving object detection in a timely fashion due to the compute-intensive nature. In this paper, we tackle the challenge by developing new techniques to substantially expedite moving object detection. We have implemented our approaches using a low-end webcam in a commodity laptop with no special hardware for high speed image processing. We have compared the performance of our approaches to the well-known background modeling technique. Our approaches reduce the average delay for moving object detection by up to 45.5% and decrease the memory consumption by up to approximately 14%, while supporting equally accurate detection.