5 results about "Active shape model" patented technology

The invention discloses an intelligent pavement friction performance evaluation method and system. The method comprises the steps of multi-source data acquisition, pavement image depth feature extraction, vehicle-road interaction friction performance evaluation and pavement friction performance dynamic evaluation. The invention relates to the technical field of data processing, in particular to an intelligent road surface friction performance evaluation method and system.According to the scheme, advanced vehicle-road interaction friction performance evaluation is innovatively proposed, then a vehicle-road interaction result and environmental data are combined for analysis, and accurate and comprehensive road surface friction performance evaluation is achieved; an active shape model is adopted to extract road surface macrostructure features, and an improved local binary texture method is adopted to extract road surface microstructure features, so that the accuracy of a vehicle-road interaction friction performance evaluation result is improved; a probability sparse self-attention mechanism, a distillation mechanism encoder and a one-time generation decoder are introduced to carry out an improved Transform algorithm, so that the calculation efficiency is improved, and the accuracy of a model output result is improved.

The invention discloses a facial expression recognition method based on multi-manifold learning, and belongs to the field of computer vision and pattern recognition. The method comprises the following steps: firstly, detecting a facial salient region by using an active shape model and constructing an expression database; secondly, carrying out image preprocessing on the salient region by adopting fractional Fourier transform, and strengthening features; then, extracting an identification matrix corresponding to each expression category through a multi-manifold identification analysis method, so that the intra-manifold distance between samples of the same type is minimized, and the inter-manifold distance between samples of different types is maximized; and finally, projecting the test sample to the identification space of each manifold, calculating the distance between the test sample and each manifold, and selecting the expression category corresponding to the manifold with the minimum distance as the identification result of the test sample. The method focuses on a face salient region, effectively improves the accuracy and robustness of expression recognition through 2D-FrFT preprocessing and an M2DA optimization algorithm, and can be applied to the fields of intelligent human-computer interaction, sentiment analysis and the like.

Methods and systems for segmentation of structures of interest (SOI) in a CT image post-operatively acquired with an implant user in a region of interest in which an implant is implanted. The method includes inputting the post-operatively acquired CT (Post-CT) image to trained networks to generate a dense deformation field (DDF) from the input Post-CT image to an atlas image; and warping a segmentation mesh of the SOI in the atlas image to the input Post-CT image using the DDF so as to generate the segmentation mesh of the SOI in the input Post-CT image, wherein the segmentation mesh of the SOI in the atlas image is generated by applying an active shape model-based method to the atlas image.

The application discloses a kind of intelligent pavement friction performance evaluation method and system, method includes multi-source data acquisition, pavement image depth feature extraction, vehicle-road interaction friction performance evaluation and pavement friction performance dynamic evaluation.The application relates to the field of data processing, specifically refers to a kind of intelligent pavement friction performance evaluation method and system, the scheme of the application innovatively proposes to carry out vehicle-road interaction friction performance evaluation first, then the vehicle-road interaction result is combined with environmental data to analyze, accurate and comprehensive pavement friction performance evaluation is realized;Active shape model is used to extract pavement macrostructure features, and improved local binary texture method is used to extract pavement microstructure features, to improve the accuracy of vehicle-road interaction friction performance evaluation results;The calculation efficiency is improved, and the accuracy of the model output result is improved by introducing probability sparse self-attention mechanism, distillation mechanism encoder and one-time generation decoder to improve the Transform algorithm.

The invention discloses a facial expression recognition method based on a two-dimensional multi-manifold discriminant analysis algorithm, and belongs to the field of computer vision and pattern recognition. The method comprises the following steps: firstly, extracting a face salient region by using an active shape model, adjusting the size of the face salient region, and performing frequency domain conversion through two-dimensional fractional Fourier transform; then, a local relation matrix in the manifolds and a local relation matrix between the manifolds are constructed, and an objective function is defined to reflect change information in the manifolds, similarity information in the manifolds and edge information between the manifolds; based on a difference criterion optimization mode and an entropy criterion optimization mode, calculation is carried out to obtain an identification matrix; compared with a traditional method, the method has the advantages that the saliency of the face region is fully considered, and the robustness and generalization ability of recognition are enhanced by weighing the similarity among the same kind of samples, the edge information among the different kinds of samples and the change information among the same kind of samples. Experimental results show that the method has significant advantages in the field of expression recognition.