Скачать или смотреть Accurate and Stable Monocular 3D Reconstruction without Training Data

This video shows the results of our Structure from Articulated Motion (SfAM) algorithm for articulated 3D structure recovery. SfAM recovers multiple object and motion types without training on extensive data collections. The method is built upon a general-purpose NRSfM technique while integrating a soft spatio-temporal constraint on the bone lengths. We use alternating optimization strategy to recover optimal geometry (i.e., bone proportions) together with 3D joint positions by enforcing the bone lengths consistency over a series of frames. SfAM is highly robust to noisy 2D annotations, generalizes to arbitrary objects and does not rely on training data. We believe that it brings a new perspective on the domain of monocular 3D recovery of articulated structures, including human motion capture.

More information can be found in our publication:
Kovalenko, O.; Golyanik, V.; Malik, J.; Elhayek, A.; Stricker, D.
Structure from Articulated Motion: Accurate and Stable Monocular 3D Reconstruction without Training Data. Sensors 2019, 19, 4603.

Contact: Onorina Kovalenko ([email protected])