An improved framework for automatic image mosaic

Lei, Jie; Ding, Jingting; Liu, Jilin

doi:10.1117/12.838410

Cited by 1 publication

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“…The image mosaic technology [22,23] is to stitch several overlapping images or scenes into a larger image, in which several reposted images or scenes are taken from different angles of the same camera or from the same or different angles of different cameras. At present, there are many research systems in image mosaic.…”

Section: Introductionmentioning

confidence: 99%

Multi‐camera traffic scene mosaic based on camera calibration

Song

Dai

et al. 2021

IET Computer Vision

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Recently, the traffic application based on vision in the single traffic‐monitoring scene has been widely studied and developed. However, cross‐regional research is still in its infancy. In order to help solve the application of cross‐regional traffic surveillance scenarios, this paper proposes a more reliable and accurate road scene mosaic method under multi‐camera surveillance. The mosaic road panorama contains physical information, which can be used to achieve a cross‐regional measurement. It also lays the foundation for vehicle spatial location, vehicle speed and traffic incident detection across regions. First, the mapping relationship between the three‐dimensional sub‐world coordinates and their corresponding two‐dimensional image coordinates is established by camera calibration. Second, the projection transformation relationship between two cameras is established by two sub‐world coordinate systems and their common information. Finally, we use the proposed inverse projection idea and translation vector relationship to complete the mosaic of two traffic‐monitoring road scenes. The experimental results show that the camera calibration accuracy can reach more than 97% in a single scene. The measurement accuracy of the mosaic block is over 95%. The experimental results show that the proposed method has a higher accuracy, which has great value in related theoretical research and practical applications.

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Section: Introductionmentioning

confidence: 99%