Adaptive on-line calibration for around-view monitoring system using between-camera homography estimation

Lim, Sung-Soo; Lee, Seohyung; Kim, Jun-Geon; Lee, Daeho

doi:10.1117/1.jrs.12.015014

Cited by 2 publications

(1 citation statement)

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“…In contrast, if a single camera image is used, the detection algorithm immediately works in each individual camera module. In addition, the synthesized image may contain image distortion, for example, the parking line may appear disconnected when the ground is not flat [10]. In a single camera image, this kind of image distortion is not present.…”

Section: Dataset a Label Information And Acquisition Methodsmentioning

confidence: 99%

Context-Based Parking Slot Detection With a Realistic Dataset

Choi

2020

IEEE Access

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The autonomous parking of vehicles requires the ability to accurately locate an available parking slot in the vicinity of a vehicle. Since parking slots have a variety of shapes and colors, may be occluded by obstacles, or look different due to surroundings such as lighting, accurately locating them can be a challenging task. In this paper, we propose a context-based parking slot detection method inspired by the process of a human driver finding a parking slot. Our method consists of two deep network modules: a parking context recognizer and parking slot detector. The parking context recognizer identifies the parking environment (type, angle, and availability of a parking slot), whereas the parking slot detector locates the exact position of a parking slot by multiple type-based fine-tuned detectors with rotated anchor boxes and a rotated non-maximal suppression. In addition, we release a realistic parking slot dataset, which comprises 22817 images of parking slots having various attributes and external conditions. We also propose a new evaluation metric for parking slot detection, reflecting whether a vehicle can be parked within the detected parking slot. Through comparison and ablation study in experiments, we demonstrate that our method outperformed the previous deep-learning-based methods, along with having a short operation time.

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Section: Dataset a Label Information And Acquisition Methodsmentioning

confidence: 99%