A Tracking Registration Method for Augmented Reality Based on Multi-modal Template Matching and Point Clouds

In order to overcome the defects where the surface of the object lacks sufficient texture features and the algorithm cannot meet the real-time requirements of augmented reality,a markerless augmented reality tracking registration method based on multimodal template matching and point clouds is proposed.The method first adapts the linear parallel multi-modal LineMod template matching method with scale invariance to identify the texture-less target and obtain the reference image as the key frame that is most similar to the current perspective.Then,we can obtain the initial pose of the camera and solve the problem of re-initialization because of tracking registration interruption.A point cloud-based method is used to calculate the precise pose of the camera in real time.In order to solve the problem that the traditional iterative closest point(ICP)algorithm cannot meet the real-time requirements of the system,Kdtree(k-dimensional tree)is used under the graphics processing unit(GPU)to replace the part of finding the nearest points in the original ICP algorithm to improve the speed of tracking registration.At the same time,the random sample consensus(RANSAC)algorithm is used to remove the error point pairs to improve the accuracy of the algorithm.The results show that the proposed tracking registration method has good real-time performance and robustness.

Substrate control in track registration and preservation:insights across the Triassic—Jurassic boundary in southern Africa

Tracks registration is influenced by the dynamic interplay between the pedal anatomy of the trackmaker,its behaviour,and the substrate conditions it interacts with.Differences in substrate conditions,especially those linked to grain size and moisture content,often result in the most dramatic variations in track morphology.In the upper Stormberg Group,main Karoo Basin of southern Africa,diverse trace fossils,primarily comprising Late Triassic—Early Jurassic dinosaur tracks,are preserved.Numerous studies have extensively documented individual ichnosites,investigating variations between sites over time,with recent studies suggesting that track abundance and anatomical fidelity increase up-stratigraphy.Despite the well-established link between substrate and track morphology,past studies have not specifically focused on substrate conditions,often emphasizing macro-sedimentary features instead.Here,we examine the micro-sedimentary features of track-bearing units in the upper Stormberg Group using petrographic techniques to better understand the palaeosubstrate and its effect on fossil track registration and preservation.The analysis revealed that very fine-grained sandstones and substrates modified by microbial activity tend to preserve tracks with greater abundance and/or higher anatomical fidelity.Furthermore,the prevalence of very fine-grained and microbially modified strata,and their associated track trends increases in younger stratigraphic units.Across the Triassic—Jurassic boundary in southern Africa,a boom in dinosaur track abundances is observed and credited to the proliferation of dinosaur populations during the Early Jurassic.Our findings,however,suggest that the observed local increase in track abundance(and anatomical fidelity)up-stratigraphy may be linked to substrate composition differences,which were ultimately controlled by large-scale changes in the palaeoenvironment from high-energy meandering fluvial to lower-energy aeolian-lacustrine settings in the Late Triassic and Early Jurassic,respectively.These findings have implications for global macroevolutionary patterns,palaeo-geographical reconstructions,and biostratigraphic correlations in the early Mesozoic.