About This Journal

The Photogrammetric Record is an international journal containing original, independently and rapidly refereed articles that reflect modern advancements in geomatics. Specifically contributions in photogrammetry, 3D imaging, computer vision, laser scanning, geomatics, and other related non-contact remote sensing related to geomatics are welcome. All aspects of the measurement workflow are relevant, from sensor characterisation and modelling, data acquisition, processing algorithms and product generation, to novel applications. The journal provides a record of new research which will contribute both to the advancement of geomatics knowledge and to the application of techniques in novel ways. It also seeks to stimulate debate through correspondence, and carries reviews of recent literature from the wider geomatics discipline.

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Articles

ORIGINAL ARTICLE

Indoor hierarchy relation graph construction method based on RGB-D

  •  25 May 2024

Graphical Abstract

Description unavailable

The HRG is an indoor topology graph containing indoor small-scale elements and represents the relationship between indoor spaces and elements in the vertical dimension. Which provides support for obstacle-level topological information for the application of component-level 3D real scenes.

ORIGINAL ARTICLE

A hierarchical occupancy network with multi‐height attention for vision‐centric 3D occupancy prediction

  •  18 May 2024

Graphical Abstract

Description unavailable

As shown on the left of the graphical abstract, we propose a new 3D occupancy prediction model called the HierOcc network. The inputs of HierOcc are multi-view temporal images. After passing through the backbone, a feature pyramid network is used to obtain multi-scale features of images. The image features and a set of voxel features initialized by learnable parameters are fed into transformer blocks composed of HSA and HACA. After this, the 3D feature volume corresponding to each group of temporal images will be registered and concatenated together, and further fused through a module composed of 3D convolutions. Finally, we up-sample the fused 3D feature volume to the same resolution as the ground truth, and then use a classification head to assign semantic label to each voxel. The core modules in our HierOcc are height-aware cross-attention and hierarchy self-attention. As shown in the right part of the graphical abstract, HACA transforms visual features from 2D image to 3D space and maintains global perception in the height dimension while decoupling features from different heights, whereas HSA enables dynamic information exchange among voxels on the same height plane, enhancing the results’ completeness for planar categories.

REVIEW ARTICLE

3D LiDAR SLAM: A survey

  •  13 May 2024

Graphical Abstract

Description unavailable

This paper presents a systematic LiDAR SLAM review that covers the framework, challenges, taxonomy, benchmarking, future trends, etc. It gives an in-depth overview of LiDAR SLAM methods, with brief summaries of advantages and limitations for each subcategory. It summarizes commonly used datasets, evaluation metrics, successful commercial SLAM solutions, and provides comprehensive comparisons of existing methods. It discusses the open problems and looks forward to the new development trends to provide insightful guidance for the community.

ORIGINAL ARTICLE

Hyperspectral image classification based on superpixel merging and broad learning system

  •  9 May 2024

Graphical Abstract

Description unavailable

This paper first suggests a novel parameter-free superpixel merging technique. Then a superpixel smoothing method is introduced by using merged superpixels. Finally, an effective spectral–spatial HSI classification scheme is proposed based on smoothed superpixels and a broad learning system.

More articles

The following is a list of the most cited articles based on citations published in the last three years, according to CrossRef.

Open access

GPS precise point positioning for UAV photogrammetry

  •  427-447
  •  5 November 2018

Graphical Abstract

Description unavailable

Global Positioning System (GPS) precise point positioning (PPP) constraints on fixed-wing unmanned aerial vehicle (UAV) image positions is demonstrated for photogrammetric mapping at accuracies of centimetres in planimetry and about a decimetre in height, from flights of 25-30 minutes duration. GPS PPP alleviates all spatial operating constraints associated with the installation and use of ground control points, simplifying operational logistics and enabling large-scale photogrammetric UAV mapping even in the most remote and challenging geographic locations.

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The following are the most downloaded articles from the Photogrammetric Record in 2018

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