This paper proposes a state based approach to gesture learning and recognition. Using spatial clustering and temporal alignment, each gesture is defined to be an ordered sequence ...
We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
We address the 3D volume reconstruction problem from depth adjacent sub-volumes acquired by a confocal laser scanning microscope (CLSM). Our goal is to align the sub-volumes by es...
Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an auto...
Background: The development of effective frameworks that permit an accurate diagnosis of tumors, especially in their early stages, remains a grand challenge in the field of bioinf...
Andreas Keller, Nicole Ludwig, Nicole Comtesse, An...