TY - GEN
T1 - Sobolev active contours
AU - Sundaramoorthi, Ganesh
AU - Yezzi, Anthony
AU - Mennucci, Andrea
PY - 2005
Y1 - 2005
N2 - All previous geometric active contour models that have been formulated as gradient flows of various energies use the same L2-type inner product to define the notion of gradient. Recent work has shown that this inner product induces a pathological Riemannian metric on the space of smooth curves. However, there are also undesirable features associated with the gradient flows that this inner product induces. In this paper, we reformulate the generic geometric active contour model by redefining the notion of gradient in accordance with Sobolev-type inner products. We call the resulting flows Sobolev active contours. Sobolev metrics induce favorable regularity properties in their gradient flows. In addition, Sobolev active contours favor global translations, but are not restricted to such motions. This is particularly useful in tracking applications. We demonstrate the general methodology by reformulating some standard edge-based and region-based active contour models as Sobolev active contours and show the substantial improvements gained in segmentation and tracking applications.
AB - All previous geometric active contour models that have been formulated as gradient flows of various energies use the same L2-type inner product to define the notion of gradient. Recent work has shown that this inner product induces a pathological Riemannian metric on the space of smooth curves. However, there are also undesirable features associated with the gradient flows that this inner product induces. In this paper, we reformulate the generic geometric active contour model by redefining the notion of gradient in accordance with Sobolev-type inner products. We call the resulting flows Sobolev active contours. Sobolev metrics induce favorable regularity properties in their gradient flows. In addition, Sobolev active contours favor global translations, but are not restricted to such motions. This is particularly useful in tracking applications. We demonstrate the general methodology by reformulating some standard edge-based and region-based active contour models as Sobolev active contours and show the substantial improvements gained in segmentation and tracking applications.
UR - http://www.scopus.com/inward/record.url?scp=33646552436&partnerID=8YFLogxK
U2 - 10.1007/11567646_10
DO - 10.1007/11567646_10
M3 - Conference contribution
AN - SCOPUS:33646552436
SN - 3540293485
SN - 9783540293484
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 109
EP - 120
BT - Variational, Geometric, and Level Set Methods in Computer Vision - Third International Workshop, VLSM 2005, Proceedings
T2 - 3rd International Workshop on Variational, Geometric, and Level Set Methods in Computer Vision, VLSM 2005
Y2 - 16 October 2005 through 16 October 2005
ER -