Automatic video to point cloud registration in a structure-from-motion framework

Vidal, E. Ras; Piotto, Nicola; Cordara, Giovanni; Burgos, Francisco Morán

doi:10.1109/icip.2015.7351282

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…The work demonstrated in [26] of 3D mapping and modeling using an RGB-D camera in indoor space investigates recovery from registration failures and coverage through visual inspection. A method proposed in [27] sought to integrate information from video sequences into existing reference 3D point clouds. It shows how to extract local 3D information from the video data, which allows incremental growing, refinement, and update of the existing 3D models.…”

Section: Related Workmentioning

confidence: 99%

On-Site 4-in-1 Alignment: Visualization and Interactive CAD Model Retrofitting Using UAV, LiDAR’s Point Cloud Data, and Video

Kumar

Patil

Chethana

et al. 2019

Sensors

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Acquisition of 3D point cloud data (PCD) using a laser scanner and aligning it with a video frame is a new approach that is efficient for retrofitting comprehensive objects in heavy pipeline industrial facilities. This work contributes a generic framework for interactive retrofitting in a virtual environment and an unmanned aerial vehicle (UAV)-based sensory setup design to acquire PCD. The framework adopts a 4-in-1 alignment using a point cloud registration algorithm for a pre-processed PCD alignment with the partial PCD, and frame-by-frame registration method for video alignment. This work also proposes a virtual interactive retrofitting framework that uses pre-defined 3D computer-aided design models (CAD) with a customized graphical user interface (GUI) and visualization of a 4-in-1 aligned video scene from a UAV camera in a desktop environment. Trials were carried out using the proposed framework in a real environment at a water treatment facility. A qualitative and quantitative study was conducted to evaluate the performance of the proposed generic framework from participants by adopting the appropriate questionnaire and retrofitting task-oriented experiment. Overall, it was found that the proposed framework could be a solution for interactive 3D CAD model retrofitting on a combination of UAV sensory setup-acquired PCD and real-time video from the camera in heavy industrial facilities.

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Section: Related Workmentioning

confidence: 99%

On-Site 4-in-1 Alignment: Visualization and Interactive CAD Model Retrofitting Using UAV, LiDAR’s Point Cloud Data, and Video

Kumar

Patil

Chethana

et al. 2019

Sensors

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“…Interactive loop closure is also adapted to remove the global inconsistency in frame-by-frame registration. Vidal et al 20 proposed a method to integrate information from video sequences into reference 3D point clouds. The videos are used to generate several local, denser 3D models.…”

Section: Literature Reviewmentioning

confidence: 99%

Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications

Patil

Kumar

Kim

et al. 2018

International Journal of Distributed Sensor Networks

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Acquiring the three-dimensional point cloud data of a scene using a laser scanner and the alignment of the point cloud data within a real-time video environment view of a camera is a very new concept and is an efficient method for constructing, monitoring, and retrofitting complex engineering models in heavy industrial plants. This article presents a novel prototype framework for virtual retrofitting applications. The workflow includes an efficient 4-in-1 alignment, beginning with the coordination of pre-processed three-dimensional point cloud data using a partial point cloud from LiDAR and alignment of the pre-processed point cloud within the video scene using a frame-by-frame registering method. Finally, the proposed approach can be utilized in pre-retrofitting applications by pre-generated three-dimensional computeraided design models virtually retrofitted with the help of a synchronized point cloud, and a video scene is efficiently visualized using a wearable virtual reality device. The prototype method is demonstrated in a real-world setting, using the partial point cloud from LiDAR, pre-processed point cloud data, and video from a two-dimensional camera.

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A Robust and Real-Time Full 3D Reconstruction Method Based on Multiple Kinect

Peng

Zeng

Wang

et al. 2018

Lecture Notes in Electrical Engineering

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Automatic video to point cloud registration in a structure-from-motion framework

Cited by 3 publications

References 27 publications

On-Site 4-in-1 Alignment: Visualization and Interactive CAD Model Retrofitting Using UAV, LiDAR’s Point Cloud Data, and Video

On-Site 4-in-1 Alignment: Visualization and Interactive CAD Model Retrofitting Using UAV, LiDAR’s Point Cloud Data, and Video

Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications

A Robust and Real-Time Full 3D Reconstruction Method Based on Multiple Kinect

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