Low-level Vision by Consensus in a Spatial Hierarchy of Regions

We introduce a multi-scale framework for low-level vision, where the goal is estimating physical scene values from image data---such as depth from stereo image pairs. The framework uses a dense, overlapping set of image regions at multiple scales and a "local model," such as a slanted-plane model for stereo disparity, that is expected to be valid piecewise across the visual field. Estimation is cast as optimization over a dichotomous mixture of variables, simultaneously determining which regions are inliers with respect to the local model (binary variables) and the correct co-ordinates in the local model space for each inlying region (continuous variables). When the regions are organized into a multi-scale hierarchy, optimization can occur in an efficient and parallel architecture, where distributed computational units iteratively perform calculations and share information through sparse connections between parents and children. The framework performs well on a standard benchmark for binocular stereo, and it produces a distributional scene representation that is appropriate for combining with higher-level reasoning and other low-level cues.Comment: Accepted to CVPR 2015. Project page: http://www.ttic.edu/chakrabarti/consensus

Skilled Birth Attendant Assessment In Haiti: A Pilot Project

Objective: To evaluate a cohort of graduates from a grassroots skilled birth attendant training program in Haiti to determine if they meet global standards of competency established by the International Confederation of Midwives. Design and setting: A testing instrument that included both a 50-question, multiple choice knowledge test and two emergency skills tests (postpartum hemorrhage and neonatal resuscitation) was adopted from the USAID Quality Assurance Project. A convenience sample of 30 skilled birth attendants completed the knowledge test and, of this cohort, a random sample of 18 completed the skills test. Data collection took place in Hinche, Haiti in July, 2013. Findings: On average, participants were correct for 59% of the knowledge questions, 34% of the skills steps for postpartum hemorrhage, and 39% of the skills steps for neonatal resuscitation. Conclusions: Emphasizing emergency simulation training and opportunities to refresh emergency skills periodically is recommended to ensure competency in a cohort of skilled birth attendants. This research is discussed in the context of the Haitian health care system fraught by extreme poverty, lack of basic infrastructure, and a critical shortage of healthcare workers

Review of Julia Kristeva, This Incredible Need to Believe.

Julia Kristeva, This Incredible Need to Believe. New York: Columbia University Press, 2009. 136 pp. ISBN 978023114784

Ab-Initio Study on the Hard Magnetic Properties of MnBi

We have studied the hard magnetic properties of the low-temperature phase of MnBi with first principle calculations based on the density functional theory. The calculations have been carried out on two distinct unit cell configurations MnBi and BiMn with the element in the unit cell origin named first. Our results show that these configurations are not equivalent and that MnBi describes the system better near T = 0K and the BiMn configuration describes the system better for T > 300K. The magnetic moments of both configurations agree well with experimental measurements considering both spin and orbital contributions. At high temperatures the magneto-crystalline anisotropy energy increases with increasing unit cell volume and reaches a maximum of 2:3MJ=m3 and a c=a ratio of 1:375.Comment: Presented at 20th International Conference on Magnetism (ICM2015) in Barcelona, accepted for publication. 5 pages, 2 figures, 4 table

Review of Elizabeth Bronfen, The Knotted Subject: Hysteria and Its Discontents.

Elizabeth Bronfen, The Knotted Subject: Hysteria and Its Discontents. Princeton: Princeton University Press, 1998. 472 pp. ISBN 069101230X (paperback)

Discriminative virtual views for cross-view action recognition

We propose an approach for cross-view action recognition by way of ‘virtual views’ that connect the action descriptors extracted from one (source) view to those extracted from another (target) view. Each virtual view is associated with a linear transformation of the action descriptor, and the sequence of transformations arising from the sequence of virtual views aims at bridging the source and target views while preserving discrimination among action categories. Our approach is capable of operating without access to labeled action samples in the target view and without access to corresponding action instances in the two views, and it also naturally incorporate and exploit corresponding instances or partial labeling in the target view when they are available. The proposed approach achieves improved or competitive performance relative to existing methods when instance correspondences or target labels are available, and it goes beyond the capabilities of these methods by providing some level of discrimination even when neither correspondences nor target labels exist.Engineering and Applied Science