Monocular estimation of 3D poses from a distance

Véges, Márton and Varga, Viktor: Monocular estimation of 3D poses from a distance. In: Conference of PhD Students in Computer Science, (11). pp. 114-117. (2018)

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Most 3D pose estimators only estimate egocentric coordinates where the body is centred at the origin. This is suitable for scenes with a single person but for images with interacting persons it is insufficient. We propose a monocular depth estimator for telephoto lenses to estimate 3D coordinates centred at the camera. Our method fuses a depth map predictor and a relative 3D pose estimator by means of a 3-layer neural network. We compare the algorithm with the state-of-the-art method and show a 19% improvement.

Item Type: Article
Journal or Publication Title: Conference of PhD Students in Computer Science
Date: 2018
Volume: 11
Page Range: pp. 114-117
Event Title: Conference of PhD students in computer science (11.) (2018) (Szeged)
Uncontrolled Keywords: Számítástechnika
Additional Information: Bibliogr.: p. 116-117. ; összefoglalás angol nyelven
Date Deposited: 2019. Nov. 04. 12:53
Last Modified: 2019. Nov. 04. 12:53

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