4D Reconstruction of Blooming Flowers

Abstract

Flower blooming is a beautiful phenomenon in nature as flowers open in an intricate and complex manner whereas petals bend, stretch and twist under various deformations. Flower petals are typically thin structures arranged in tight configurations withheavy self-occlusions. Thus, capturing and reconstructing spatially and temporally coherent sequences of blooming flowers is highly challenging. Early in the process only exterior petals are visible and thus interior parts will be completely missing in the captured data. Utilizing commercially available 3D scanners, we capture the visible parts of blooming flowers into a sequence of 3D point clouds. We reconstruct the flower geometry and deformation over time using a template-based dynamic tracking algorithm. To track and model interior petals hidden in early stages of the blooming process, we employ an adaptively constrained optimization. Flower characteristics are exploited to track petals both forward and backward in time. Our methods allow us to faithfully reconstruct the flower blooming process of different species. In addition, we provide comparisons with state-of-the-art physical simulation-based approaches and evaluate our approach by using photos of captured real flowers.or image-based measurements taken at sparse intervals. Such workflows are tedious, prone to measurement bias and difficult to scale to large-scale observations, both in space and time.Advances in affordable three-dimensional (3D) acquisition devices now provide new opportunities in capturing and modelling 3D real-life phenomena in time. For instance, Li et al. [LFM*13] proposed a method for detecting bifurcations of indoor plants from 4D point cloud data. The problem of reconstructing 4D sequences of blooming flowers, however, is considerably more challenging. During the flower opening, inner petals, which were previously occluded, appear and commence an intricate deformation process. Throughout this process, petals may stretch, bend and finally shrink and wrinkle, while possibly colliding with other flower structures.

Geometry Reconstruction of Plants

“…In a similar type of work, Zheng et al [42] presented an algorithm to dynamically track a blooming flower over time. The idea is based on the reconstruction of flower geometry and deformation of the model over time via a template model.…”

Warp-and-project tomography for rapidly deforming objects

“…Priors on motion are also integrated. In [Li et al 2013;Zheng et al 2017] a 3D scanner is used to capture 4D point cloud data, which is used respectively to reconstruct the plant growth and the flower blooming process. Furthermore, some approaches were developed for the capture of time-varying fluid surfaces, where specific priors to the fluid field are usually incorporated [Wang et al 2009].…”

Modelling and Simulation of Lily flowers using PDE Surfaces

“…Hence, they cannot produce realistic effects such as wrinkles and shrinking. Recently, Zheng et al [15] proposed a template-based dynamic tracking algorithm to capturing blooming flower sequences from 3D scanners. This technique provides the motion information for different petals, which is represented as a set of transformations.…”