VRFromX: From Scanned Reality to Interactive Virtual Experience with Human-in-the-Loop

VRFromX: From Scanned Reality to Interactive Virtual Experience with Human-in-the-Loop

There is an increasing trend of Virtual-Reality (VR) applications found in education, entertainment, and industry. Many of them utilize real world tools, environments, and interactions as bases for creation. However, creating such applications is tedious, fragmented,...
First-Person View Hand Segmentation of Multi-Modal Hand Activity Video Dataset

First-Person View Hand Segmentation of Multi-Modal Hand Activity Video Dataset

Abstract:  First-person-view videos of hands interacting with tools are widely used in the computer vision industry. However, creating a dataset with pixel-wise segmentation of hands is challenging since most videos are captured with fingertips occluded by the hand...
A Large-scale Annotated Mechanical Components Benchmark for Classification and Retrieval Tasks with Deep Neural Networks

A Large-scale Annotated Mechanical Components Benchmark for Classification and Retrieval Tasks with Deep Neural Networks

We introduce a large-scale annotated mechanical components benchmark for classification and retrieval tasks named Mechanical Components Benchmark (MCB): a large-scale dataset of 3D objects of mechanical components. The dataset enables data-driven feature learning for...
CAPturAR: An Augmented Reality Tool for Authoring Human-Involved Context-Aware Applications

CAPturAR: An Augmented Reality Tool for Authoring Human-Involved Context-Aware Applications

Recognition of human behavior plays an important role in context-aware applications. However, it is still a challenge for end-users to build personalized applications that accurately recognize their own activities. Therefore, we present CAPturAR, an in-situ...