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Optimized Long Short-Term Memory Network for LiDAR-Based Vehicle Trajectory Prediction Through Bayesian Optimization
In vehicle trajectory prediction, traditional methods like Kalman filtering often rely heavily on user expertise and prior knowledge, while newer deep learning approaches, such as Long Short-Term Memory (LSTM) networks, also face challenges related to human intervention and subjective hyperparameter selection. This study proposes a systematic approach for Light Detection and Ranging (LiDAR)-based ...Show More
Relightable Detailed Human Reconstruction from Sparse Flashlight Images
Jiawei Lu;Tianjia Shao;He Wang;Yong-Liang Yang;Yin Yang;Kun Zhou
IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Early Access Article |
We present a lightweight system for reconstructing human geometry and appearance from sparse flashlight images. Our system produces detailed geometry including garment wrinkles and surface reflectance, which are exportable for direct rendering and relighting in traditional graphics pipelines. By capturing multi-view flashlight images using a consumer camera equipped with an co-located LED (e.g., a...Show More
DCOR: Dynamic Channel-Wise Outlier Removal to De-Noise LiDAR Data Corrupted by Snow
Since the past decade, Light Detection and Ranging (LiDAR) data have been extensively adopted for traffic object recognition tasks. Existing methodologies often assume LiDAR data are acquired under normal weather conditions. Nevertheless, many researchers have observed that the LiDAR data captured under inclement weather are often contaminated with noises such as fog and snow, which may deteriorat...Show More
Augmented Incremental Potential Contact for Sticky Interactions
Yu Fang;Minchen Li;Yadi Cao;Xuan Li;Joshuah Wolper;Yin Yang;Chenfanfu Jiang
We introduce a variational formulation for simulating sticky interactions between elastoplastic solids. Our method brings a wider range of material behaviors into the reach of the Incremental Potential Contact (IPC) solver recently developed by (Li et al. 2020). Extending IPC requires several contributions. We first augment IPC with the classical Raous-Cangemi-Cocou (RCC) adhesion model. This allo...Show More
Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision
Feng Luo;Ling Liu;G. Geoff Wang;Vijay Kumar;Mark S. Ashton;Jacob Abernethy;Fatemeh Afghah;Matthew H. E. M Browning;David Coyle;Philip Dames;Tom O'Halloran;James Hays;Patrick Heisl;Chenfanfu Jiang;Puskar Khanal;Venkat Narayan Krovi;Sara Kuebbing;Nianyi Li;JingJing Liang;Ninghao Liu;Steve McNulty;Christopher M. Oswalt;Neil Pederson;Demetri Terzopoulos;Christopher W. Woodall;Yongkai Wu;Jian Yang;Yin Yang;Liang Zhao
2023 IEEE 5th International Conference on Cognitive Machine Intelligence (CogMI)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Forests and forest ecosystems are vital to our social, economic, and environmental well-being. However, climate change and climate-driven disturbances (CDDs) are undermining the health and resilience of forests worldwide and pose significant uncertainty to sustainable forest management. Climate-smart forestry (CSF) remains a grand challenge in practice due to our limited knowledge of how forests r...Show More
Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision
Feng Luo;Ling Liu;G. Geoff Wang;Vijay Kumar;Mark S. Ashton;Jacob Abernethy;Fatemeh Afghah;Matthew H. E. M Browning;David Coyle;Philip Dames;Tom O'Halloran;James Hays;Patrick Heisl;Chenfanfu Jiang;Puskar Khanal;Venkat Narayan Krovi;Sara Kuebbing;Nianyi Li;JingJing Liang;Ninghao Liu;Steve McNulty;Christopher M. Oswalt;Neil Pederson;Demetri Terzopoulos;Christopher W. Woodall;Yongkai Wu;Jian Yang;Yin Yang;Liang Zhao
Year: 2023 | Conference Paper |
Leveraging Deep Convolutional Neural Networks Pre-Trained on Autonomous Driving Data for Vehicle Detection From Roadside LiDAR Data
Recent technological advancements in computer vision algorithms and data acquisition devices have greatly facilitated the research and applications of deep learning-based traffic object recognition from Light Detection and Ranging (LiDAR) data. The majority of existing methodologies applied deep learning (DL)-based techniques, especially Convolutional Neural Networks (CNNs), for vehicle detection ...Show More
Computational Design of Skinned Quad-Robots
Xudong Feng;Jiafeng Liu;Huamin Wang;Yin Yang;Hujun Bao;Bernd Bickel;Weiwei Xu
We present a computational design system that assists users to model, optimize, and fabricate quad-robots with soft skins. Our system addresses the challenging task of predicting their physical behavior by fully integrating the multibody dynamics of the mechanical skeleton and the elastic behavior of the soft skin. The developed motion control strategy uses an alternating optimization scheme to av...Show More
H-CNN: Spatial Hashing Based CNN for 3D Shape Analysis
We present a novel spatial hashing based data structure to facilitate 3D shape analysis using convolutional neural networks (CNNs). Our method builds hierarchical hash tables for an input model under different resolutions that leverage the sparse occupancy of 3D shape boundary. Based on this data structure, we design two efficient GPU algorithms namely hash2col and col2hash so that the CNN operati...Show More
NNWarp: Neural Network-Based Nonlinear Deformation
Ran Luo;Tianjia Shao;Huamin Wang;Weiwei Xu;Xiang Chen;Kun Zhou;Yin Yang
NNWarp is a highly re-usable and efficient neural network (NN) based nonlinear deformable simulation framework. Unlike other machine learning applications such as image recognition, where different inputs have a uniform and consistent format (e.g., an array of all the pixels in an image), the input for deformable simulation is quite variable, high-dimensional, and parametrization-unfriendly. Conse...Show More
Taxi-Based Mobility Demand Formulation and Prediction Using Conditional Generative Adversarial Network-Driven Learning Approaches
Hao Yu;Xiaofeng Chen;Zhenning Li;Guohui Zhang;Pan Liu;Jinfu Yang;Yin Yang
In this paper, a deep learning (DL) framework was proposed to predict the taxi-passenger demand while the spatial, the temporal, and external dependencies were considered simultaneously. The proposed DL framework combined a modified density-based spatial clustering algorithm with noise (DBSCAN) and a conditional generative adversarial network (CGAN) model. More specifically, the modified DBSCAN mo...Show More
A Kinect-Based Approach for 3D Pavement Surface Reconstruction and Cracking Recognition
Yuming Zhang;Cong Chen;Qiong Wu;Qi Lu;Su Zhang;Guohui Zhang;Yin Yang
Pavement surface distress conditions are critical inputs for quantifying roadway infrastructure serviceability. Numerous computer-aided automatic examination techniques have been deployed for pavement distress condition assessments, such as digital image processing methods. However, their effectiveness and applicability are impeded due to information losses in 2-D image combination processes or ex...Show More
Force-Driven Traffic Simulation for a Future Connected Autonomous Vehicle-Enabled Smart Transportation System
Recent technology advances significantly push forward the development and the deployment of the concept of smart, such as smart community and smart city. Smart transportation is one of the core components in modern urbanization processes. Under this context, the connected autonomous vehicle (CAV) system presents a promising solution towards the enhanced traffic safety and mobility through state-of...Show More
Physics-Based Quadratic Deformation Using Elastic Weighting
This paper presents a spatial reduction framework for simulating nonlinear deformable objects interactively. This reduced model is built using a small number of overlapping quadratic domains as we notice that incorporating high-order degrees of freedom (DOFs) is important for the simulation quality. Departing from existing multi-domain methods in graphics, our method interprets deformed shapes as ...Show More
Acoustic VR in the mouth: A real-time speech-driven visual tongue system
Ran Luo;Qiang Fang;Jianguo Wei;Wenhuan Lu;Weiwei Xu;Yin Yang
We propose an acoustic-VR system that converts acoustic signals of human language (Chinese) to realistic 3D tongue animation sequences in real time. It is known that directly capturing the 3D geometry of the tongue at a frame rate that matches the tongue's swift movement during the language production is challenging. This difficulty is handled by utilizing the electromagnetic articulography (EMA) ...Show More
Contour-based 3D tongue motion visualization using ultrasound image sequences
Kele Xu;Yin Yang;Clémence Leboullenger;Pierre Roussel;Bruce Denby
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2016 | Conference Paper |
Cited by: Papers (4)
This article describes a contour-based 3D tongue deformation visualization framework using B-mode ultrasound image sequences. A robust, automatic tracking algorithm characterizes tongue motion via a contour, which is then used to drive a generic 3D Finite Element Model (FEM). A novel contour-based 3D dynamic modeling method is presented. Modal reduction and modal warping techniques are applied to ...Show More
Haptic simulation of needle-tissue interaction based on shape matching
2014 IEEE International Symposium on Haptic, Audio and Visual Environments and Games (HAVE) Proceedings
Year: 2014 | Conference Paper |
Cited by: Papers (5)
Simulating needle-tissue interaction in a haptic-enabled environment is an essential component in many virtual surgical training procedures, where the trainee would practice needle insertion and retraction repeatedly. Efficiency and stability are of major importance for the corresponding visual and haptic rendering. In this paper, we present a novel system for a real-time and robust simulation of ...Show More
Haptic-enabled interactive rendering of deformable objects based on shape matching
2013 IEEE International Symposium on Haptic Audio Visual Environments and Games (HAVE)
Year: 2013 | Conference Paper |
Cited by: Papers (9)
In this paper, we propose a novel framework to simulate 3D deformation of flexible objects in real time with haptic interaction as well as force rendering. The deformation is computed using the shape matching method, which is a meshless geometry-based approach and well known for the simplicity and robustness. We introduce new mechanism named Constraint Particle Coupling for the real time deformabl...Show More
Distributed Haptic Interactions with Physically Based 3D Deformable Models over Lossy Networks
IEEE Transactions on Haptics
Cited by: Papers (4)
Researchers have faced great challenges when simulating complicated 3D volumetric deformable models in haptics-enabled collaborative/cooperative virtual environments (HCVEs) due to the expensive simulation cost, heavy communication load, and unstable network conditions. When general network services are applied to HCVEs, network problems such as packet loss, delay, and jitter can cause severe visu...Show More
Boundary-Aware Multidomain Subspace Deformation
In this paper, we propose a novel framework for multidomain subspace deformation using node-wise corotational elasticity. With the proper construction of subspaces based on the knowledge of the boundary deformation, we can use the Lagrange multiplier technique to impose coupling constraints at the boundary without overconstraining. In our deformation algorithm, the number of constraint equations t...Show More
Physics-Based Deformable Tongue Visualization
Yin Yang;Xiaohu Guo;Jennell Vick;Luis G. Torres;Thomas F. Campbell
In this paper, a physics-based framework is presented to visualize the human tongue deformation. The tongue is modeled with the Finite Element Method (FEM) and driven by the motion capture data gathered during speech production. Several novel deformation visualization techniques are presented for in-depth data analysis and exploration. To reveal the hidden semantic information of the tongue deform...Show More
Physics-based multi-domain subspace deformation with component mode synthesis
2012 IEEE Virtual Reality Workshops (VRW)
Year: 2012 | Conference Paper |
Fast and accurate simulation of 3D soft objects is important to virtual environment and reality. Simulating 3D deformation of large model in real-time is a challenging problem as it is very computation-demanding involving intensive matrix-based operation of large scale. Reduction techniques, consequently flourish where the dynamic is computed within a subspace of much smaller size with accuracy lo...Show More
Real-Time GPU-Aided Lung Tumor Tracking
Yin Yang;Zichun Zhong;Guodong Rong;Xiaohu Guo;Jing Wang;Timothy Solberg;Weihua Mao
2010 Fourth Pacific-Rim Symposium on Image and Video Technology
Year: 2010 | Conference Paper |
Cited by: Papers (4)
A real time solution of tracking daily lung tumor motion is proposed in this paper in order to achieve an accurate dose delivery for radiation therapy as recently developed cone-beam computed tomography (CBCT) technique is not able to catch tumor motions due to the patient's respiration. We develop a novel GPU-based fast digitally reconstructed radiograph (DRR) generation algorithm which enables a...Show More
On supporting collaborative haptic interactions with physically-based 3D deformations
2010 IEEE International Symposium on Haptic Audio Visual Environments and Games
Year: 2010 | Conference Paper |
Haptic-enabled collaborative systems have long been limited to 3D rigid models only, primarily due to slow force calculations, long-time deformable simulations and large communication loads. In this paper, we propose a novel system to support real-time sharing of haptic feedbacks and deformable simulations of physically-based 3D models in a distributed virtual environment. Particularly, adopting a...Show More
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