The smart home appliances are dramatically growing into a big part of the consumer electronics market and they are required to have many convenient functions for users. Therefore, many products are using top-view imaging systems for advanced technologies to recognize object positions and movement for human and machine interaction. Although the topview imaging system has already developed for many applications, not only home appliances but also closed-circuit televisions (CCTV) and unmanned aerial vehicles (UAV), it still has many drawbacks. Especially the top-view image shows asymmetrical features and radially distorted scenes around the corners like omnidirectional view images. Therefore, conventional human detection methods are struggled with the computational complexity and low accuracy to calibrate its artifacts. In this paper, we propose an efficient method to recognize spatial domain of human positions and movements based on motion vector detection using multiple feature maps on the top-view images. In the experimental results, we show efficient computation time and results of spatial domain detection qualitatively.