3D Reconstruction Market By Key Players, Deployment Type, Applications

The global 3D reconstruction market (henceforth, referred to as the market studied) was valued at USD 756.7 million in 2019, and it is expected to reach USD 1197.9 million by 2025, registering a CAGR of 7.96% during 2020-2025. 3D reconstruction can be used across a wide range of applications, including art analysis and restoration, phenotype analysis, film, and game graphics, and design, among others. Furthermore, the projections of application related to end users and the commercial sector have been among the prominent factors prompting vendors to invest in technology developments.

3D reconstruction of buildings had been an active research topic in computer vision, as well as in digital photogrammetry, during the past years. 3D building models are gaining increasing popularity in the areas of urban planning, tourism, etc.

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Additionally, the advent of deep learning techniques and, most importantly, the increased availability of large training data sets led to a new generation of methods that can recover the 3D geometry and structure of objects, either from one or several RGB images, without using any complex camera calibration process. The image-based 3D reconstruction is an important problem and a building block to several applications, ranging from autonomous navigation and robotics to graphics and entertainment

Key Market Trends

3D Reconstruction Software Segment is Expected to Gain the Largest Share

– With technological advancements and product innovations, 3D printing technology is being applied in a wide variety of areas, due to which a significant number of reconstruction software solutions for multi-view images are being adopted. The software solutions used in a wide variety of applications are GIS applications, cultural heritage, media and entertainment, manufacturing, healthcare, etc.
– For 3D reconstruction, various approaches, such as 123D Catch, PhotoScan, photo tourism, VideoTrace, KinectFusion, and ProFORMA, with various inputs, like image collections, single images, and video footage, are in use. Each approach has its own drawbacks; for instance, if stereo vision is used, depth information, only up to a limited distance, of typically less than 5 meters is available for the reconstruction process. Furthermore, currently, 3D reconstructions have issues with, e.g., shiny, textureless, or occluded surfaces.
– Additionally, 3D reconstruction and 3D rendering technology help in visualizing 3D models representing neuron morphology, for fluorescent confocal images that help in providing accurate and complete characterizations. With this technology, reconstruction of a single neuron with sub-micron resolution or large neuron system with a feature size of millimeters is possible.

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Christophe Rude

Christophe Rude

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