A method for acquiring at least one bounding box corresponding to at least one object in a test image by using a convolutional neural network, CNN, including a tracking network, comprising steps of: (a) acquiring by a testing device multiple proposal boxes, wherein a feature map is generated as a result of applying convolution operation to the test image as a current frame, and outputting information on the multiple proposal boxes from a Region Proposal Network, RPN by using the feature map; (b) selecting by the testing device at least one specific proposal box among the multiple proposal boxes by referring to (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, wherein the proposal box having the smallest distance is selected as the at least one specific proposal box, or (ii) a result of comparing each of scores as probability values which indicates whether each of the proposal boxes includes the object, wherein the proposal box having the highest score is selected as the at least one specific proposal box, and then setting the specific proposal box as a starting area of a tracking box, wherein the starting area is used for a mean shift tracking algorithm, wherein the score is represented by a ratio of a region corresponding to an intersection of an area of a ground truth bounding box and that of each of the proposal boxes to a region corresponding to a union of the area of the GT bounding box and that of each of the proposal boxes; (c) determining by the testing device a specific area of the current frame having information on probability most similar to information on probability 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; (d) allowing by the testing device 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 fully connected, FC layer, to acquire the bounding box by applying regression operation to the pooled feature map; and (e) determining by the testing device the bounding box as a reference bounding box to be used for a tracking box of the object to be located in a next frame. (a) acquiring by a testing device multiple proposal boxes, wherein a feature map is generated as a result of applying convolution operation to the test image as a current frame, and outputting information on the multiple proposal boxes from a Region Proposal Network, RPN by using the feature map; (b) selecting by the testing device at least one specific proposal box among the multiple proposal boxes by referring to (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, wherein the proposal box having the smallest distance is selected as the at least one specific proposal box, or (ii) a result of comparing each of scores as probability values which indicates whether each of the proposal boxes includes the object, wherein the proposal box having the highest score is selected as the at least one specific proposal box, and then setting the specific proposal box as a starting area of a tracking box, wherein the starting area is used for a mean shift tracking algorithm, wherein the score is represented by a ratio of a region corresponding to an intersection of an area of a ground truth bounding box and that of each of the proposal boxes to a region corresponding to a union of the area of the GT bounding box and that of each of the proposal boxes; (c) determining by the testing device a specific area of the current frame having information on probability most similar to information on probability 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; (d) allowing by the testing device 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 fully connected, FC layer, to acquire the bounding box by applying regression operation to the pooled feature map; and (e) determining by the testing device the bounding box as a reference bounding box to be used for a tracking box of the object to be located in a next frame.