TY - GEN
T1 - Visual estimation of object density distribution through observation of its impulse response
AU - Mkhitaryan, Artashes
AU - Burschka, Darius
PY - 2013
Y1 - 2013
N2 - In this paper we introduce a novel vision based approach for estimating physical properties of an object such as its center of mass and mass distribution. Passive observation only allows to approximate the center of mass with the centroid of the object. This special case is only true for objects that consist of one material and have unified mass distribution. We introduce an active interaction technique with the object derived from the analogon to system identification with impulse functions. We treat the object as a black box and estimate its internal structure by analyzing the response of the object to external impulses. The impulses are realized by striking the object at points computed based on its external geometry. We determine the center of mass from the profile of the observed angular motion of the object that is captured by a high frame-rate camera. We use the motion profiles from multiple strikes to compute the mass distribution. Knowledge of these properties of the object leads to more energy efficient and stable object manipulation. As we show in our real world experiments, our approach is able to estimate the intrinsic layered density structure of an object.
AB - In this paper we introduce a novel vision based approach for estimating physical properties of an object such as its center of mass and mass distribution. Passive observation only allows to approximate the center of mass with the centroid of the object. This special case is only true for objects that consist of one material and have unified mass distribution. We introduce an active interaction technique with the object derived from the analogon to system identification with impulse functions. We treat the object as a black box and estimate its internal structure by analyzing the response of the object to external impulses. The impulses are realized by striking the object at points computed based on its external geometry. We determine the center of mass from the profile of the observed angular motion of the object that is captured by a high frame-rate camera. We use the motion profiles from multiple strikes to compute the mass distribution. Knowledge of these properties of the object leads to more energy efficient and stable object manipulation. As we show in our real world experiments, our approach is able to estimate the intrinsic layered density structure of an object.
KW - Active exploration
KW - Motion analysis
KW - Object categorization
UR - http://www.scopus.com/inward/record.url?scp=84878245927&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84878245927
SN - 9789898565471
T3 - VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
SP - 586
EP - 595
BT - VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
T2 - 8th International Conference on Computer Vision Theory and Applications, VISAPP 2013
Y2 - 21 February 2013 through 24 February 2013
ER -