Terrain Simplification Research in Augmented Scene Modeling

Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.

Structured scene modeling using micro stereo vision system with large field of view

This paper presents a method for structured scene modeling using micro stereo vision system with large field of view. The proposed algorithm includes edge detection with Canny detector, line fitting with principle axis based approach, finding corresponding lines using feature based matching method, and 3D line depth computation.

Fuzzy-based indoor scene modeling with differentiated examples

Well-designed indoor scenes incorporate interior design knowledge,which has been an essential prior for most indoor scene modeling methods.However,the layout qualities of indoor scene datasets are often uneven,and most existing data-driven methods do not differentiate indoor scene examples in terms of quality.In this work,we aim to explore an approach that leverages datasets with differentiated indoor scene examples for indoor scene modeling.Our solution conducts subjective evaluations on lightweight datasets having various room configurations and furniture layouts,via pairwise comparisons based on fuzzy set theory.We also develop a system to use such examples to guide indoor scene modeling using user-specified objects.Specifically,we focus on object groups associated with certain human activities,and define room features to encode the relations between the position and direction of an object group and the room configuration.To perform indoor scene modeling,given an empty room,our system first assesses it in terms of the user-specified object groups,and then places associated objects in the room guided by the assessment results.A series of experimental results and comparisons to state-of-the-art indoor scene synthesis methods are presented to validate the usefulness and effectiveness of our approach.

Perspectives on point cloud-based 3D scene modeling and XR presentation within the cloud-edge-client architecture

With the support of edge computing,the synergy and collaboration among central cloud,edge cloud,and terminal devices form an integrated computing ecosystem known as the cloud-edge-client architecture.This integration unlocks the value of data and computational power,presenting significant opportunities for large-scale 3D scene modeling and XR presentation.In this paper,we explore the perspectives and highlight new challenges in 3D scene modeling and XR presentation based on point cloud within the cloud-edge-client integrated architecture.We also propose a novel cloud-edge-client integrated technology framework and a demonstration of municipal governance application to address these challenges.

Sparsity-based efficient simulation of cluster targets electromagnetic scattering

An efficient and real-time simulation method is proposed for the dynamic electromagnetic characteristics of cluster targets to meet the requirements of engineering practical applications.First,the coordinate transformation method is used to establish a geometric model of the observation scene,which is described by the azimuth angles and elevation angles of the radar in the target reference frame and the attitude angles of the target in the radar reference frame.Then,an approach for dynamic electromagnetic scattering simulation is proposed.Finally,a fast-computing method based on sparsity in the time domain,space domain,and frequency domain is proposed.The method analyzes the sparsity-based dynamic scattering characteristic of the typical cluster targets.The error between the sparsity-based method and the benchmark is small,proving the effectiveness of the proposed method.

Multi-source data-based 3D digital preservation of large scale ancient chinese architecture:A case report

The 3D digitalization and documentation of ancient Chinese architecture is challenging because of architectural complexity and structural delicacy.To generate complete and detailed models of this architecture,it is better to acquire,process,and fuse multi-source data instead of single-source data.In this paper,we describe our work on 3D digital preservation of ancient Chinese architecture based on multi source data.We first briefly introduce two surveyed ancient Chinese temples,Foguang Temple and Nanchan Temple.Then,we report the data acquisition equipment we used and the multi-source data we acquired.Finally,we provide an overview of several applications we conducted based on the acquired data,including ground and aerial image fusion,image and LiDAR(light detection and ranging)data fusion,and architectural scene surface reconstruction and semantic modeling.We believe that it is necessary to involve multi-source data for the 3D digital preservation of ancient Chinese architecture,and that the work in this paper will serve as a heuristic guideline for the related research communities.

Modeling diurnal variation of ground thermal radiance images using energy balance model and endmember composing technique

Modeling and analyzing dynamic changes of land thermal radiance scenes play an important role in thermal remote sensing. In this paper, the diurnal variation of ground surface thermal scene is mainly discussed. Firstly, based on the land surface energy balance equation, the diurnal variation of land surface temperatures （LSTs） over bare land covers were simulated by an analyt- ical thermal model with second harmonic terms, and the diurnal LST variation of vegetation canopy was simulated using the Cupid model. Secondly, normalized difference vegetation index （NDVI）, normalized difference water index （NDWI）, and ratio resident-area index （RRI） were used to evaluate the endmember abundance of four land cover types including vegetation, bare soil, impervious and water area, which were calculated from IKONOS visible and near infrared （VNIR） bands. Finally, the thermal radiance scenes at various times and view angles were modeled based on the linear-energy-mixing hypothesis. The re- suits showed that the simulated daily LST variations for vegetated and bare surfaces are correlated with the measured values with a maximum standard deviation of 2.7℃, that land thermal radiant textures with high-resolution are restored from the lin- ear-energy-mixing method, and that the information abundance of the scene are related to the distribution of land cover, the imaging time, and the view angle.

Hand Interface in Traditional Modeling and Animation Tasks

3-D task space in modeling and animation is usually reduced to the separate control dimensions supported by conventional interactive devices. This limitation maps only patial view of the problem to the device space at a time, and results in tedious and un natural interface of control. This paper uses the DataGlove interface for modeling and animating scene behaviors. The modeling interface selects, scales, rotates, translates,copies and deletes the instances of the prindtives. These basic modeling processes are directly performed in the task spacet using hand shapes and motions. Hand shapes are recoginzed as discrete states that trigger the commands, and hand motion are mapped to the movement of a selected instance. The interactions through hand interface place the user as a participant in the process of behavior simulation. Both event triggering and role switching of hand are experimented in simulation. The event mode of hand triggers control signals or commands through a menu interface. The object mode of hand simulates itself as an object whose appearance or motion inlluences the motions of other objects in scene. The involvement of hand creates a diversity of dyndric situations for testing variable scene behaviors. Our experiments have shown the potential use of this interface directly in the 3-D modeling and animation task space.

Dynamic background modeling using tensor representation and ant colony optimization

Background modeling and subtraction is a fundamental problem in video analysis. Many algorithms have been developed to date, but there are still some challenges in complex environments, especially dynamic scenes in which backgrounds are themselves moving, such as rippling water and swaying trees. In this paper, a novel background modeling method is proposed for dynamic scenes by combining both tensor representation and swarm intelligence. We maintain several video patches, which are naturally represented as higher order tensors,to represent the patterns of background, and utilize tensor low-rank approximation to capture the dynamic nature. Furthermore, we introduce an ant colony algorithm to improve the performance. Experimental results show that the proposed method is robust and adaptive in dynamic environments, and moving objects can be perfectly separated from the complex dynamic background.