Application of 3D range camera in virtual human-computer interfaces

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In recent years, there has been a significant revolution in the field of deep learning, which has demonstrated its effectiveness in automatically capturing intricate patterns from large datasets. However, the majority of these successes in Computer Vision ...

We interact with the world through a body that includes hands and fingers. Likewise, providing an avatar allowing the control of a virtual body with fingers is an important step to improve the user experience in VR. When the user and their avatar skeleton ...

Hand gestures are one of the most natural and expressive way for humans to convey information, and thus hand gesture recognition has become a research hotspot in the human-machine interface (HMI) field. In particular, biological signals such as surface ele ...

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

This toolkit has everything you need to perform imaging with a lensless camera. We make use of a low-cost implementation of DiffuserCam, namely replacing the lens with a piece of tape and using the Raspberry Pi HQ camera sensor. Similar principles and meth ...

To predict the response of masonry buildings to various types of loads, engineers use finite element models, specifically solid-element and macro-element models. For predicting masonry responses to seismic events in particular, equivalent frame models-a su ...

Megapixel single-photon avalanche diode (SPAD) arrays have been developed recently, opening up the possibility of deploying SPADs as general-purpose passive cameras for photography and computer vision. However, most previous work on SPADs has been limited ...

Cross-resolution face recognition has become a challenging problem for modern deep face recognition systems. It aims at matching a low-resolution probe image with high-resolution gallery images registered in a database. Existing methods mainly leverage pri ...

Object detection plays a critical role in various computer vision applications, encompassing domains like autonomous vehicles, object tracking, and scene understanding. These applica- tions rely on detectors that generate bounding boxes around known object ...

Region extraction is a very common task in both Computer Science and Engineering with several applications in object recognition and motion analysis, among others. Most of the literature focuses on regions delimited by straight lines, often in the special ...

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

Application of 3D range camera in virtual human-computer interfaces

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Deep Learning for 3D Surface Modelling and Reconstruction

Real-time Self-contact Retargeting of Avatars down to Finger Level

Motor-Unit Ordering of Blindly-Separated Surface-EMG Signals for Gesture Recognition

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

LenslessPiCam: A Hardware and Software Platform for Lensless Computational Imaging with a Raspberry Pi

Automated image-based generation of finite element models for masonry buildings

Seeing Photons in Color

Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation

Improving Object Detection under Domain Shifts

Region Extraction in Mesh Intersection

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Universal and adaptive methods for robust stochastic optimization