AI Medical Compendium Journal:
IEEE transactions on visualization and computer graphics

Showing 51 to 60 of 74 articles

Spatio-Temporal Manifold Learning for Human Motions via Long-Horizon Modeling.

IEEE transactions on visualization and computer graphics
Data-driven modeling of human motions is ubiquitous in computer graphics and computer vision applications, such as synthesizing realistic motions or recognizing actions. Recent research has shown that such problems can be approached by learning a nat...

Disentangled Human Body Embedding Based on Deep Hierarchical Neural Network.

IEEE transactions on visualization and computer graphics
Human bodies exhibit various shapes for different identities or poses, but the body shape has certain similarities in structure and thus can be embedded in a low-dimensional space. This article presents an autoencoder-like network architecture to lea...

A Steering Algorithm for Redirected Walking Using Reinforcement Learning.

IEEE transactions on visualization and computer graphics
Redirected Walking (RDW) steering algorithms have traditionally relied on human-engineered logic. However, recent advances in reinforcement learning (RL) have produced systems that surpass human performance on a variety of control tasks. This paper i...

Live Semantic 3D Perception for Immersive Augmented Reality.

IEEE transactions on visualization and computer graphics
Semantic understanding of 3D environments is critical for both the unmanned system and the human involved virtual/augmented reality (VR/AR) immersive experience. Spatially-sparse convolution, taking advantage of the intrinsic sparsity of 3D point clo...

DGaze: CNN-Based Gaze Prediction in Dynamic Scenes.

IEEE transactions on visualization and computer graphics
We conduct novel analyses of users' gaze behaviors in dynamic virtual scenes and, based on our analyses, we present a novel CNN-based model called DGaze for gaze prediction in HMD-based applications. We first collect 43 users' eye tracking data in 5 ...

Weakly Supervised Adversarial Learning for 3D Human Pose Estimation from Point Clouds.

IEEE transactions on visualization and computer graphics
Point clouds-based 3D human pose estimation that aims to recover the 3D locations of human skeleton joints plays an important role in many AR/VR applications. The success of existing methods is generally built upon large scale data annotated with 3D ...

Facetto: Combining Unsupervised and Supervised Learning for Hierarchical Phenotype Analysis in Multi-Channel Image Data.

IEEE transactions on visualization and computer graphics
Facetto is a scalable visual analytics application that is used to discover single-cell phenotypes in high-dimensional multi-channel microscopy images of human tumors and tissues. Such images represent the cutting edge of digital histology and promis...

ProtoSteer: Steering Deep Sequence Model with Prototypes.

IEEE transactions on visualization and computer graphics
Recently we have witnessed growing adoption of deep sequence models (e.g. LSTMs) in many application domains, including predictive health care, natural language processing, and log analysis. However, the intricate working mechanism of these models co...

DeepOrganNet: On-the-Fly Reconstruction and Visualization of 3D / 4D Lung Models from Single-View Projections by Deep Deformation Network.

IEEE transactions on visualization and computer graphics
This paper introduces a deep neural network based method, i.e., DeepOrganNet, to generate and visualize fully high-fidelity 3D / 4D organ geometric models from single-view medical images with complicated background in real time. Traditional 3D / 4D m...

A Natural-language-based Visual Query Approach of Uncertain Human Trajectories.

IEEE transactions on visualization and computer graphics
Visual querying is essential for interactively exploring massive trajectory data. However, the data uncertainty imposes profound challenges to fulfill advanced analytics requirements. On the one hand, many underlying data does not contain accurate ge...