title: Isomap transform for segmenting human body shapes.
abstract: Segmentation of the 3D human body is a very challenging problem in applications exploiting volume capture data. Direct clustering in the Euclidean space is usually complex or even unsolvable. This paper presents an original method based on the Isomap (isometric feature mapping) transform of the volume data-set. The 3D articulated posture is mapped by Isomap in the pose of Da Vinci's Vitruvian man. The limbs are unrolled from each other and separated from the trunk and pelvis, and the topology of the human body shape is recovered. In such a configuration, Hoshen-Kopelman clustering applied to concentric spherical shells is used to automatically group points into the labelled principal curves. Shepard interpolation is utilised to back-map points of the principal curves into the original volume space. The experimental results performed on many different postures have proved the validity of the proposed method. Reliability of less than 2 cm and 3° in the location of the joint centres and direction axes of rotations has been obtained, respectively, which qualifies this procedure as a potential tool for markerless motion analysis.
authors.affiliation: Bioengineering Department , Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano, Italy. pietro.cerveri@polimi.it
authors.forename: P
authors.initials: P
authors.lastname: Cerveri
authors.forename: K J
authors.initials: KJ
authors.lastname: Sarro
authors.forename: M
authors.initials: M
authors.lastname: Marchente
authors.forename: R M L
authors.initials: RM
authors.lastname: Barros
mesh_terms: D018594:Human Body; D006801:Humans; D008954:Models, Biological