公开(公告)号：US20230377172A1

公开(公告)日：2023-11-23

申请号：US18080726

申请日：2022-12-13

Applicant: FENG CHIA UNIVERSITY

Inventor： KUAN-HUNG CHEN

IPC: G06T7/246 ,  G06V20/50 ,  G06V10/77

CPC classification number: G06T7/246 ,  G06V20/50 ,  G06V10/7715 ,  G06T2207/30241 ,  G06T2207/20084

Abstract: The present invention provides an object automatic tracking system, which includes an image capturing device, a computing device and a display device, and the computing device includes a first computing module and a second computing module. The captured-in image is converted into a frame data and determined as either the first data or the second data according to the type of each frame. The first data is to obtain a property information and a location information of each target object in the image; and the second data is to obtain the trajectory information of each target object. Finally, the property information, the location information and the trajectory information are combined and output to the display device.

公开(公告)号：US20230359887A1

公开(公告)日：2023-11-09

申请号：US18080703

申请日：2022-12-13

Applicant: FENG CHIA UNIVERSITY

Inventor： KUAN-HUNG CHEN ,  DE-SHENG CHEN

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: The present invention provides an automatic labeling system and operating method thereof. The automatic labeling system comprises a data access end, a CPU and a GPU. The CPU may co-operate with the GPU to use the data which is saved in the data access end for training neural network models, and therefore to create automatic prediction algorithms which are used to process and label different types of data automatically. Therefore, the present invention is able to establish object detection datasets, semantic segmentation datasets and tracking datasets automatically. On the other hand, the present invention further provides a quantitative evaluation tool which is used for evaluating the trained neural network models.