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Pose Machines provide a sequential prediction framework for learning rich implicit spatial models. In this work we show a systematic design for how convolutional networks can be incorporated into the pose machine framework for learning image features and image-dependent spatial models for the task of pose estimation. The contribution of this paper is to(More)
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, affordance(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)
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)
This paper presents a method for acquiring dense nonrigid 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)
In the preceding paper we have demonstrated an increase in presentation of both major histocompatibility complex antigens (MHC) and a tumor-associated antigen of the weakly immunogenic B16 melanoma by a straight-forward technique. The method consists in modulating the tumor cell membrane by hydrostatic pressure and simultaneous chemical crosslinking of the(More)
Delayed-type hypersensitivity (DTH) to the chemically induced EL4 and virally induced ARadLV 136 leukemia cells was determined by the radioactive ear test. Prior to the DTH test, mice were prevaccinated with cells treated either with hydrostatic pressure or with the membrane-impermeant crosslinker adenosine dialdehyde or with a combination of these. For(More)
The B16-BL6 melanoma, like most spontaneously arising tumors, is poorly immunogenic and expresses low levels of major histocompatibility complex (MHC) antigens. Treatment of cells of this tumor in vitro by hydrostatic pressure in the presence of adenosine 2',3'-dialdehyde (oxAdo), a membrane-impermeant crosslinker, caused elevated projection of MHC and a(More)