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Found 13 papers, 0 papers with code
Two-step registration in 3D human body scanning based on multiple RGB-D sensors
In this paper, we propose a universal registration method for the body scanner consists of multiple fixed sensors.
Automatic body measurement based on slicing loops
The purpose of this paper is to propose a new method of body measurement based on the loop structure.
Automatic foot scanning and measurement based on multiple RGB-depth cameras
In this paper, a system with six depth cameras was built to scan both feet simultaneously.
A study on improving the calibration of body scanner built on multiple RGB-Depth cameras
Purpose The calibration is a key but cumbersome process for 3D body scanning using multiple depth cameras.
3D textile reconstruction based on KinectFusion and synthesized texture
Purpose The purpose of this paper is to present a novel framework of reconstructing the 3D textile model with synthesized texture.
Foot shape prediction using elliptical Fourier analysis
In this paper, a new method was proposed to establish the relationship between three-dimensional (3D) foot shapes and their two-dimensional (2D) foot silhouettes, through which a complete 3D foot shape can be predicted by simply inputting its two 2D silhouettes.
Personalized 3D mannequin reconstruction based on 3D scanning
A personalized mannequin is essential for apparel customization using CAD technologies.
Automatic three-dimensional-scanned garment fitting based on virtual tailoring and geometric sewing
The patches of the three-dimensional garment were automatically positioned around the human model by setting up the correspondence via feature matching.
Revised Progressive-Hedging-Algorithm Based Two-layer Solution Scheme for Bayesian Reinforcement Learning
Stochastic control with both inherent random system noise and lack of knowledge on system parameters constitutes the core and fundamental topic in reinforcement learning (RL), especially under non-episodic situations where online learning is much more demanding.
BERT-based Financial Sentiment Index and LSTM-based Stock Return Predictability
On the other hand, by combining with the other two commonly-used methods when it comes to building the sentiment index in the financial literature, i. e., the option-implied and the market-implied approaches, we propose a more general and comprehensive framework for the financial sentiment analysis, and further provide convincing outcomes for the predictability of individual stock return by combining LSTM (with a feature of a nonlinear mapping).
Scenario-decomposition Solution Framework for Nonseparable Stochastic Control Problems
When stochastic control problems do not possess separability and/or monotonicity, the dynamic programming pioneered by Bellman in 1950s fails to work as a time-decomposition solution method.
Optimization and Control Systems and Control Systems and Control Portfolio Management
Tackling A Class of Hard Subset-Sum Problems: Integration of Lattice Attacks with Disaggregation Techniques
Subset-sum problems belong to the NP class and play an important role in both complexity theory and knapsack-based cryptosystems, which have been proved in the literature to become hardest when the so-called density approaches one.
Integrating Different Informations for Portfolio Selection
Following the idea of Bayesian learning via Gaussian mixture model, we organically combine the backward-looking information contained in the historical data and the forward-looking information implied by the market portfolio, which is affected by heterogeneous expectations and noisy trading behavior.
