1. A method for acquiring at least one bounding box corresponding to at least one object in a test image by using a CNN including a tracking network, comprising steps of: (a) a testing device acquiring or supporting another device to acquire multiple proposal boxes, if feature map is generated as a result of applying convolution operation to the test image as a current frame, and then information on the multiple proposal boxes by applying certain operation to the feature map by a Region Proposal Network (RPN) is outputted; (b) the testing device selecting or supporting another device to select at least one specific proposal box among the multiple proposal boxes by referring to at least either of (i) a result of comparing each distance between a reference bounding box of the object in a previous frame and each of the multiple proposal boxes and (ii) a result of comparing each of scores as probability values which indicates whether each of the proposal boxes includes the object, and then setting or another device to set the specific proposal box as a starting area of a tracking box, wherein the starting area is used for a mean shift tracking algorithm; (c) the testing device determining or supporting another device to determine a specific area of the current frame having information on probability similar to that corresponding to pixel data of the object in the previous frame as a target area of the tracking box by using the mean shift tracking algorithm; and (d) the testing device allowing a pooling layer to generate a pooled feature map by applying pooling operation to an area in the feature map corresponding to the specific area and then allowing a FC layer to acquire a bounding box by applying regression operation to the pooled feature map.