Object Detection: Algorithms and Prospects | IEEE Conference Publication | IEEE Xplore

Object Detection: Algorithms and Prospects


Abstract:

As one of the most fundamental and challenging problems in computer vision, object detection has received tremendous attention in recent years. Its development over the p...Show More

Abstract:

As one of the most fundamental and challenging problems in computer vision, object detection has received tremendous attention in recent years. Its development over the past two decades can be seen as a microcosm of the history of computer vision. The goal of face detection is to find the corresponding positions of all the faces in the image. The output of the algorithm is the coordinates of the circumscribing rectangle of the face in the image, and may also include information such as attitude such as tilt angle. Algorithms are constantly updated to address higher accuracy, lower computational complexity, and faster detection. In view of the development of object detection technology, this paper introduces six different algorithms, R-CNN, fast R-CNN, faster R-CNN, YOLO, corner net, and Neural Architecture Search (NAS), to accomplish the purpose of detection. We finally provide the future prospect of object detection in several direction, which can give a further analysis for this area and hope to help the individuals who get started in object detection.
Date of Conference: 15-16 August 2022
Date Added to IEEE Xplore: 15 December 2022
ISBN Information:
Conference Location: Zakopane, Poland

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