@conference {cLin15,
	title = {Time consistent estimation of End-effectors from RGB-D data},
	booktitle = {Image and Video Technology: 7th Pacific-Rim Symposium, PSIVT 2015, Auckland, New Zealand, November 25-27, 2015, Revised Selected Papers},
	number = {9431},
	year = {2015},
	month = {12/2015},
	pages = {529-543},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {<p>End-effectors are usually related to the location of the free end of a kinematic chain. Each of them contains rich structure information about the entity. Hence, estimating stable end-effectors of different entities enables robust tracking as well as a generic representation. In this paper, we present a system for end-effector estimation from RGB-D stream data. Instead of relying on a specific pose or configuration for initialization, we exploit time coherence without making any assumption with respect to the prior knowledge. This makes the estimation process more robust in a predict-update framework. Qualitative and quantitative experiments are performed against the reference method with promising results.</p>},
	keywords = {End-effector estimation; Time coherence; Topology representation},
	isbn = {978-3-319-29451-3},
	doi = {10.1007/978-3-319-29451-3_42},
	author = {X. Lin and Casas, J. and M. Pard{\`a}s}
}
