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Improvement of Pose Estimation using Integrated NMS with Rotated Images
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- Authors
- Dohun Kim, Wonjong Kim
- Issue Date
- 2023-06
- Citation
- International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) 2023, pp.718-721
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Pose estimation is a challenging problem in computer vision, which involves estimating the position and orientation of objects in an image. Non-Maximum Suppression (NMS) is a widely used technique to suppress multiple detections of the same object in an image. However, in some cases, NMS can lead to a loss of accurate pose estimation. In this paper, we propose an integrated NMS approach with rotated images to improve pose estimation accuracy. Our approach involves rotating the image and applying NMS to the rotated image to suppress multiple detections. We then rotate the suppressed detections back to the original image and estimate the pose of the object. We evaluate our proposed approach on MPII benchmark datasets, and the results show that our approach improves 8% in mAP compared to YOLO V7
- KSP Keywords
- Benchmark datasets, Computer Vision(CV), Estimation accuracy, Non-maximum suppression, Orientation of objects, Pose estimation, Position and orientation