Boundary detection is a fundamental computer vision problem that is essential for a variety of tasks, such as contour and region segmentation, symmetry detection and object recognition and categorization. We propose a generalized formulation for boundary detection, with closed-form solution, applicable to the localization of different types of boundaries, such as object edges in natural images and occlusion boundaries from video. Our generalized boundary detection method (Gb) simultaneously combines low-level and mid-level image representations in a single eigenvalue problem and solves for the optimal continuous boundary orientation and strength. The closed-form solution to boundary detection enables our algorithm to achieve state of the art results at a significantly lower computational cost than current methods. We also propose two complementary novel components that can seamlessly be combined with Gb: first, we introduce a soft-segmentation procedure that provides region input layers to our boundary detection algorithm for a significant improvement in accuracy, at negligible computational cost; second, we present an efficient method for contour grouping and reasoning, which when applied as a final post-processing stage, further increases the boundary detection performance.
 Marius Leordeanu, Rahul Sukthankar and Cristian Sminchisescu. "Efficient closed-form solution to generalized boundary detection." European Conference on Computer Vision (ECCV), Florence, Italy, 2012. PDF
 Marius Leordeanu, Rahul Sukthankar and Cristian Sminchisescu. "Generalized Boundaries from Multiple Image Interpretations", submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013.
 Marius Leordeanu, Rahul Sukthankar and Cristian Sminchisescu, "Generalized Boundaries from Multiple Image Interpretations", arXiv:1202.3684 (2012). PDF
MATLAB code for Gb Boundary Detector, Soft-Segmentation and Contour Reasoning are available here.
for questions or bugs you could email Marius Leordeanu at leordeanu at gmail.
 E. Trulls, I. Kokkinos, A. Sanfeliu and F. Moreno-Noguer, "Dense Segmentation-aware Descriptors", Computer Vision and Pattern Recognition (CVPR), 2013. Access the project website here.