Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
스테레오 비전을 이용한 합성곱 기반 실시간 깊이맵 생성 기법. (Korean) |
| Alternate Title: |
Real-Time Depth Map Using Stereo Vision and Convolutional Filtering. (English) |
| Συγγραφείς: |
이현중, 박대진 |
| Πηγή: |
Journal of the Korea Institute of Information & Communication Engineering; Sep2025, Vol. 29 Issue 9, p1251-1260, 10p |
| Θεματικοί όροι: |
Depth maps (Digital image processing), Stereo vision (Computer science), Detectors, Autonomous vehicles, Depth perception, Spatial filters, Object recognition (Computer vision) |
| Περίληψη: |
In autonomous driving systems, accurate perception of the surrounding environment and appropriate decision-making require reliable acquisition of 3D spatial information. Although LiDAR-based 3D mapping technologies have been widely used, they face several limitations and difficulty in integrating with vehicle platforms. To address these issues, this study proposes a real-time depth map generation method that relies on stereo vision, offering a cost-effective alternative to expensive sensors. The proposed approach effectively detects object boundaries, removes unnecessary non-object regions connected to the background, and calculates depth by directly matching disparity between frame elements within object regions. In the process, a convolution filter is used to enhance pixel uniqueness. This approach achieves superior real-time performance over traditional and deep learning-based techniques without requiring complex computation or costly sensors. Thus, it serves as a low-cost, high-efficiency alternative suitable for autonomous vehicles and embedded vision systems. [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of the Korea Institute of Information & Communication Engineering is the property of Korea Institute of Information & Communication Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Βάση Δεδομένων: |
Complementary Index |