DeepAI AI Chat
Log In Sign Up

RGBD-Dog: Predicting Canine Pose from RGBD Sensors

04/16/2020
by   Sinead Kearney, et al.
University of Bath
UNIST
18

The automatic extraction of animal 3D pose from images without markers is of interest in a range of scientific fields. Most work to date predicts animal pose from RGB images, based on 2D labelling of joint positions. However, due to the difficult nature of obtaining training data, no ground truth dataset of 3D animal motion is available to quantitatively evaluate these approaches. In addition, a lack of 3D animal pose data also makes it difficult to train 3D pose-prediction methods in a similar manner to the popular field of body-pose prediction. In our work, we focus on the problem of 3D canine pose estimation from RGBD images, recording a diverse range of dog breeds with several Microsoft Kinect v2s, simultaneously obtaining the 3D ground truth skeleton via a motion capture system. We generate a dataset of synthetic RGBD images from this data. A stacked hourglass network is trained to predict 3D joint locations, which is then constrained using prior models of shape and pose. We evaluate our model on both synthetic and real RGBD images and compare our results to previously published work fitting canine models to images. Finally, despite our training set consisting only of dog data, visual inspection implies that our network can produce good predictions for images of other quadrupeds – e.g. horses or cats – when their pose is similar to that contained in our training set.

READ FULL TEXT

page 1

page 3

page 4

page 7

page 8

page 13

page 14

page 15

07/31/2021

SyDog: A Synthetic Dog Dataset for Improved 2D Pose Estimation

Estimating the pose of animals can facilitate the understanding of anima...
09/21/2020

Synthetic Training for Accurate 3D Human Pose and Shape Estimation in the Wild

This paper addresses the problem of monocular 3D human shape and pose es...
12/11/2019

VIBE: Video Inference for Human Body Pose and Shape Estimation

Human motion is fundamental to understanding behavior. Despite progress ...
06/18/2021

hSMAL: Detailed Horse Shape and Pose Reconstruction for Motion Pattern Recognition

In this paper we present our preliminary work on model-based behavioral ...
10/10/2018

Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time

We demonstrate a novel deep neural network capable of reconstructing hum...
11/14/2018

Creatures great and SMAL: Recovering the shape and motion of animals from video

We present a system to recover the 3D shape and motion of a wide variety...
12/02/2021

Hierarchical Neural Implicit Pose Network for Animation and Motion Retargeting

We present HIPNet, a neural implicit pose network trained on multiple su...

Code Repositories

RGBD-Dog

Code and data repository for RGB-Dog CVPR 2020 paper


view repo