1. A method for detecting multiple objects from real-time images, comprising: performing, using a central processing unit (CPU) host, an image segmentation process to divide real-time input images into a plurality of image partitions; allocating a multitude of image memory according to the plurality of image partitions for parallel computation in a plurality of graphics processing units (GPUs); performing, by registration kernels of the plurality of GPUs, a fast block-wise registration process to register the plurality of image partitions; performing, by mask setting kernels of the plurality of GPUs, a mark setting process for the registered image partitions to stitch the registered images into output images; performing, by background generation kernels of the plurality of GPUs, a background generation process based on the output images to generate background images through median filter; performing, by foreground generation kernels of the plurality of GPUs, a foreground generation process based on the output images to generate foreground images based on a Hyper-Q computation framework; performing, by classification kernels of the plurality of GPUs, a support vector machine classification process to classify a plurality of objects of the real-time input images; and generating, by the CPU host, visualization classification images based on the background images, foreground images and the plurality of objects.