Human skeleton tracking from depth data using geodesic distances and optical flow

By L. Schwarz, Artashes Mkhitaryan, D. Mateus, Nassir Navab. 2012

210 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Space-Time Representation of People Based on 3D Skeletal Data: A Review (2016, methodology): “[64] Geodesic distance & optical flow Depth and RGB image streams 3D skeleton, 16 joints, robust to occlusions”
3D Gestural Interaction: The State of the Field (2013, background): “Other recent approaches that make use of depth cameras to track the whole body can be found in [46] [47] [48].”
Body Surface Context: A New Robust Feature for Action Recognition From Depth Videos (2014, background): “Unfortunately, depth-image-capture devices [8]–[10] are seldom adopted in action recognition due to low speed, low resolution, inconvenience, and high cost.”