Detail of publication

Abstract

We present new software for hand pose estimation from a depth image. The software won the HANDS19 Challenge in Task 2. HANDS19 Challenge is a public competition designed for the evaluation of the task of 3D hand pose estimation in both depth and colour modalities in the presence and absence of objects. Task 2 was focused on Depth-Based 3D Hand Pose Estimation while Interacting with Objects. This task builds on F-PHAB dataset. Objects appear being manipulated by a subject in an egocentric viewpoint. The main goals of the challenge are to assess the performance of state of the art approaches in terms of interpolation-extrapolation capabilities of hand variations in their main four axes (shapes, articulations, viewpoints, objects), and the use of synthetic data to fill the gaps of current datasets on these axes. The challenge consists of a standardized dataset, an evaluation protocol for three different tasks and a public competition. Participating methods were analyzed and ranked according to their performance on the mentioned axes. Winners and prizes were announced and awarded during the International Conference on Computer Vision (ICCV) 2019 workshop and results will be disseminated in a subsequent challenge publication.