7,540 research outputs found
Manifold Constrained Low-Rank Decomposition
Low-rank decomposition (LRD) is a state-of-the-art method for visual data
reconstruction and modelling. However, it is a very challenging problem when
the image data contains significant occlusion, noise, illumination variation,
and misalignment from rotation or viewpoint changes. We leverage the specific
structure of data in order to improve the performance of LRD when the data are
not ideal. To this end, we propose a new framework that embeds manifold priors
into LRD. To implement the framework, we design an alternating direction method
of multipliers (ADMM) method which efficiently integrates the manifold
constraints during the optimization process. The proposed approach is
successfully used to calculate low-rank models from face images, hand-written
digits and planar surface images. The results show a consistent increase of
performance when compared to the state-of-the-art over a wide range of
realistic image misalignments and corruptions
A graphical model based solution to the facial feature point tracking problem
In this paper a facial feature point tracker that is motivated by applications
such as human-computer interfaces and facial expression analysis systems is
proposed. The proposed tracker is based on a graphical model framework. The
facial features are tracked through video streams by incorporating statistical relations in time as well as spatial relations between feature points. By exploiting the spatial relationships between feature points, the proposed method provides robustness in real-world conditions such as arbitrary head movements and occlusions. A Gabor feature-based occlusion detector is developed and used to handle occlusions. The performance of the proposed tracker has been evaluated
on real video data under various conditions including occluded facial gestures
and head movements. It is also compared to two popular methods, one based
on Kalman filtering exploiting temporal relations, and the other based on active
appearance models (AAM). Improvements provided by the proposed approach
are demonstrated through both visual displays and quantitative analysis
Measuring and modeling the perception of natural and unconstrained gaze in humans and machines
Humans are remarkably adept at interpreting the gaze direction of other individuals in their surroundings. This skill is at the core of the ability to engage in joint visual attention, which is essential for establishing social interactions. How accurate are humans in determining the gaze direction of others in lifelike scenes, when they can move their heads and eyes freely, and what are the sources of information for the underlying perceptual processes? These questions pose a challenge from both empirical and computational perspectives, due to the complexity of the visual input in real-life situations. Here we measure empirically human accuracy in perceiving the gaze direction of others in lifelike scenes, and study computationally the sources of information and representations underlying this cognitive capacity. We show that humans perform better in face-to-face conditions compared with recorded conditions, and that this advantage is not due to the availability of input dynamics. We further show that humans are still performing well when only the eyes-region is visible, rather than the whole face. We develop a computational model, which replicates the pattern of human performance, including the finding that the eyes-region contains on its own, the required information for estimating both head orientation and direction of gaze. Consistent with neurophysiological findings on task-specific face regions in the brain, the learned computational representations reproduce perceptual effects such as the Wollaston illusion, when trained to estimate direction of gaze, but not when trained to recognize objects or faces.This work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF – 1231216
Heterogeneity in Surface Sensing Suggests a Division of Labor in Pseudomonas aeruginosa Populations
The second messenger signaling molecule cyclic diguanylate monophosphate (c-di-GMP) drives the transition between planktonic and biofilm growth in many bacterial species. Pseudomonas aeruginosa has two surface sensing systems that produce c-di-GMP in response to surface adherence. Current thinking in the field is that once cells attach to a surface, they uniformly respond by producing c-di-GMP. Here, we describe how the Wsp system generates heterogeneity in surface sensing, resulting in two physiologically distinct subpopulations of cells. One subpopulation has elevated c-di-GMP and produces biofilm matrix, serving as the founders of initial microcolonies. The other subpopulation has low c-di-GMP and engages in surface motility, allowing for exploration of the surface. We also show that this heterogeneity strongly correlates to surface behavior for descendent cells. Together, our results suggest that after surface attachment, P. aeruginosa engages in a division of labor that persists across generations, accelerating early biofilm formation and surface exploration
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Guidelines for the use of cell lines in biomedical research
Cell-line misidentification and contamination with microorganisms, such as mycoplasma, together with instability, both genetic and phenotypic, are among the problems that continue to affect cell culture. Many of these problems are avoidable with the necessary foresight, and these Guidelines have been prepared to provide those new to the field and others engaged in teaching and instruction with the information necessary to increase their awareness of the problems and to enable them to deal with them effectively. The Guidelines cover areas such as development, acquisition, authentication, cryopreservation, transfer of cell lines between laboratories, microbial contamination, characterisation, instability and misidentification. Advice is also given on complying with current legal and ethical requirements when deriving cell lines from human and animal tissues, the selection and maintenance of equipment and how to deal with problems that may arise
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