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Reconstructing an arbitrary configuration of 3D points from their projection in an image is an ill-posed problem. When the points hold semantic meaning, such as anatomical landmarks on a body, human observers can often infer a plausible 3D configuration, drawing on extensive visual memory. We present an activity-independent method to recover the 3D(More)
The human body is structurally symmetric. Tracking by detection approaches for human pose suffer from double counting, where the same image evidence is used to explain two separate but symmetric parts, such as the left and right feet. Double counting, if left unaddressed can critically affect subsequent processes, such as action recognition, af-fordance(More)
Predicting the Software reliability is a pertinent issue and it is a major concern of software developers and engineers in changing environment considerations. Software reliability models are developed to estimate the probability of failure free operation of the software for a long time. Many Software Reliability Growth Models (SRGM) were developed to give(More)
State-of-the-art approaches for articulated human pose estimation are rooted in parts-based graphical models. These models are often restricted to tree-structured representations and simple parametric potentials in order to enable tractable inference. However, these simple dependencies fail to capture all the interactions between body parts. While models(More)
This paper presents a method for acquiring dense non-rigid shape and deformation from a single monocular depth sensor. We focus on modeling the human hand, and assume that a single rough template model is available. We combine and extend existing work on model-based tracking , subdivision surface fitting, and mesh deformation to acquire detailed hand models(More)
Representing uncertainty in predictions made by complex probabilistic models is often crucial but computationally challenging. There are a number of useful prob-abilistic models where computing the most probably assignment (or MAP) is easy but finding the marginal probability of variables is hard. In this paper, we present a novel representation of(More)
We present a simple approach for producing a small number of structured visual outputs which have high recall, for a variety of tasks including monocular pose estimation and semantic scene segmentation. Current state-of-the-art approaches learn a single model and modify inference procedures to produce a small number of diverse predictions. We take the(More)
We evaluate the performance of a widely used tracking-by-detection and data association multi-target tracking pipeline applied to an activity-rich video dataset. In contrast to traditional work on multi-target pedestrian tracking where people are largely assumed to be upright, we use an activity-rich dataset that includes a wide range of body poses derived(More)
The economic dispatch problem with valve point loading effects may cause a small change in the objective function formulation. Due to valve point loading effects mechanism, complexity will come into picture and some other additionalities will include. Hence, we use strong optimization techniques to determine the minimum fuel cost for generation. The(More)