A biologically inspired appearance model for robust visual tracking

In this work, we propose a biologically inspired appearance model for robust visual tracking. Motivated in part by the success of the hierarchical organization of the primary visual cortex (area V1), we establish an architecture consisting of five layers: whitening, rectification, normalization, coding and polling. The first three layers stem from the models developed for object recognition. In this paper, our attention focuses on the coding and pooling layers. In particular, we use a discriminative sparse coding method in the coding layer along with spatial pyramid representation in the pooling layer, which makes it easier to distinguish the target to be tracked from its background in the presence of appearance variations. An extensive experimental study shows that the proposed method has higher tracking accuracy than several state-of-the-art trackers.

New Organizational Leadership: Nonstate Actors in Global Economic Governance

States and international organizations have found irresistible cause in a globalizing world to coopt nonstate actors (NGOs, private standard setters and so forth) to manage the manifold problems arising under their stretched mandates and resources. The pooling of capacities in the pursuit of common goals seems perfectly sensible. Yet although the strategy of cooptation has become a policy of choice, policy makers often lack full knowledge of its implications. As Philip Selznick first showed, cooptation can have unintended consequences, shifting leadership from one organization to another. We place this fertile insight in a better specified analytical framework. That is, one capable of explaining when and how leadership shifts occur and where the status quo leaders will remain at the helm. Using original interview data and structured focused comparisons to test the framework, we reveal dramatic variation in leadership changes following the cooptation of outside actors in global financial and environmental governance.