Spatiotemporal human representation based on 3D visual perception data is a rapidly
growing research area. Representations can be broadly categorized into two groups …

Movement dataset reviews exist but are limited in coverage, both in terms of size and
research discipline. While topic-specific reviews clearly have their merit, it is critical to have a …

We present the first end-to-end solution to create high-quality free-viewpoint video encoded
as a compact data stream. Our system records performances using a dense set of RGB and …

Most recent approaches to monocular 3D pose estimation rely on Deep Learning. They
either train a Convolutional Neural Network to directly regress from image to 3D pose, which …

In this work, we present an approach to fuse video with sparse orientation data obtained
from inertial sensors to improve and stabilize full-body human motion capture. Even though …

Human pose estimation is one of the most popular research topics in the past two decades,
especially with the introduction of human pose datasets for benchmark evaluation. These …

This paper proposes a temporal tracking algorithm based on Random Forest that uses depth
images to estimate and track the 3D pose of a rigid object in real-time. Compared to the state …

Next generation smart and augmented reality systems demand a computational
understanding of monocular footage that captures humans in physical spaces to reveal …

US10431000B2 - Robust mesh tracking and fusion by using part-based key frames and priori
model - Google Patents US10431000B2 - Robust mesh tracking and fusion by using part-based …

We address the problem of instruction selection in code generation for embedded DSP
microprocessors. Such processors have highly irregular data-paths, and conventional code …