Multi-instance Methods for Partially Supervised Image Segmentation [chapter]

Andreas Müller, Sven Behnke
2012 Lecture Notes in Computer Science  
In this paper, we propose a new partially supervised multiclass image segmentation algorithm. We focus on the multi-class, singlelabel setup, where each image is assigned one of multiple classes. We formulate the problem of image segmentation as a multi-instance task on a given set of overlapping candidate segments. Using these candidate segments, we solve the multi-instance, multi-class problem using multi-instance kernels with an SVM. This computationally advantageous approach, which requires
more » ... only convex optimization, yields encouraging results on the challenging problem of partially supervised image segmentation.
doi:10.1007/978-3-642-28258-4_12 fatcat:a5knctennjbahcnqxbld7e33s4