5 results about "Structure from motion" patented technology

Systems, methods, and computer program code for motion segmentation using a motion from structure approach; and related image processing tasks. Structure-from-motion systems are also described. In some implementations feature representations for pixels of an image frame are used to extrapolate from high reliability regions to lower reliability regions, based on semantic similarity as represented by the feature representations. This can link different visible parts of the same object, e.g. for generating a segmentation map for moving objects.

This invention discloses a Gaussian splashing method for dynamic scenes based on spatiotemporal motion distillation. It outputs a set of sparse point clouds from images at different viewpoints and times through a motion inference structure. The sparse point clouds are used to initialize Gaussian point attributes. The initialized Gaussian point set undergoes a fixed number of pre-training iterations to obtain a standard spatial set. Learnable motion feature representations are introduced into the Gaussian point attributes to explicitly model the spatiotemporal motion of the Gaussian points. Motion anchor points are extracted by distilling the motion information of the Gaussian points. During the iteration process, an adaptive density control mechanism continuously updates the density distribution of the Gaussian points, outputting the corresponding Gaussian model and deformation field weights for subsequent rendering evaluation. This invention fully utilizes the spatiotemporal characteristics of dynamic objects to efficiently reconstruct and render dynamic scenes, effectively solving the artifact and noise problems that occur during dynamic scene rendering, thereby outputting high-quality rendered images.

The application discloses a plant phenotype-oriented three-dimensional reconstruction method and a collection system. The method first acquires multi-view image data of a plant through a 360-degree ring collection system integrated with an RGB camera and a depth camera; then generates an accurate foreground mask by using a foreground semantic segmentation model; then combines structure from motion (SfM) and depth point cloud, and performs fusion under the guidance of the foreground mask to obtain an initial point cloud; then performs mask-guided 3D Gaussian splashing (3DGS) optimization reconstruction based on the point cloud, and the optimization process improves the identification of small plant organs by using a mask weighted loss function and a semantic-guided density control strategy; and finally derives a color point cloud from the optimized Gaussian model, which can be directly used for extraction of phenotype parameters such as plant height and leaf area. The application solves the problems of large noise and detail loss in the prior art when reconstructing plants in a complex background, and realizes fast three-dimensional reconstruction which can be directly used for phenotype analysis.

The invention discloses a bridge damage positioning and quantifying method based on unmanned aerial vehicle panoramic unfolding and TCFormer driving, and the method comprises the steps: 1) unmanned aerial vehicle image collection: employing a matrix type flight path planning strategy, and dividing a bridge bottom into a plurality of independent collection regions; 2) panorama construction: performing single-component three-dimensional reconstruction on the acquired image through a motion recovery structure SfM and a multi-view stereoscopic vision MVS technology; 3) performing multi-class damage segmentation: performing semantic segmentation on the panoramic image cutting area based on a lightweight TCFormer model; 4) component-level positioning: establishing a standardized component coordinate system and an index system, and dividing the components into five types; according to the method, a health evaluation system including PMCI single component scoring and PCCI whole-span comprehensive scoring is constructed, full-process automation from image acquisition, damage identification, spatial positioning, geometric quantification to health evaluation is achieved, and the efficiency, precision and standardization level of bridge detection are improved.

Embodiments of the present disclosure provide an unmanned aerial vehicle image block adjustment positioning method and device for irregular large area uniform block. The method comprises: acquiring a set of unmanned aerial vehicle images and POS data; acquiring geographical range information of a shooting area of the set of unmanned aerial vehicle images according to the POS data; performing block on the set of unmanned aerial vehicle images based on the geographical range information of the shooting area to obtain a set of unmanned aerial vehicle image blocks; performing pose estimation on each unmanned aerial vehicle image block in the set of unmanned aerial vehicle image blocks according to a structure from motion (SfM) algorithm to obtain a set of unmanned aerial vehicle image block information; performing global coordinate conversion on the set of unmanned aerial vehicle image block information to obtain a set of rough unmanned aerial vehicle image block information in a global coordinate system; and performing global block adjustment calculation on the set of rough unmanned aerial vehicle image block information to obtain final global three-dimensional coordinates of a physical point and global unmanned aerial vehicle image pose parameter information. The present application reduces the problem of block adjustment failure in pose solution caused by error accumulation through an adaptive block method.