Current Issue : July - September Volume : 2016 Issue Number : 3 Articles : 4 Articles
In this paper, we investigate articulated human\nmotion tracking from video sequences using Bayesian\napproach.We derive a generic particle-based filtering procedure\nwith a low-dimensional manifold. The manifold can be\ntreated as a regularizer that enforces a distribution over poses\nduring tracking process to be concentrated around the low dimensional\nembedding.We refer to our method as manifold\nregularized particle filter.We present a particular implementation\nof our method based on back-constrained gaussian\nprocess latent variable model and gaussian diffusion. The\nproposed approach is evaluated using the real-life benchmark\ndataset HumanEva. We show empirically that the presented\nsampling scheme outperforms sampling-importance resampling\nand annealed particle filter procedures....
With the rapid development and application of CRFs (Conditional Random Fields) in computer vision, many researchers have made\nsome outstanding progress in this domain because CRFs solve the classical version of the label bias problem with respect to MEMMs\n(maximum entropy Markov models) and HMMs (hidden Markov models). This paper reviews the research development and status\nof object recognition with CRFs and especially introduces two main discrete optimization methods for image labeling with CRFs:\ngraph cut and mean field approximation.This paper describes graph cut briefly while it introduces mean field approximation more\ndetailedly which has a substantial speed of inference and is researched popularly in recent years....
The paper proposes a method for the detection\nof bubble-like transparent objects in a liquid. The detection\nproblem is non-trivial since bubble appearance varies\nconsiderably due to different lighting conditions causing contrast\nreversal and multiple interreflections.We formulate the\nproblem as the detection of concentric circular arrangements\n(CCA). The CCAs are recovered in a hypothesize-optimizeverify\nframework. The hypothesis generation is based on\nsampling from the partially linked components of the nonmaximum\nsuppressed responses of oriented ridge filters,\nand is followed by the CCA parameter estimation. Parameter\noptimization is carried out by minimizing a novel\ncost-function. The performance was tested on gas dispersion\nimages of pulp suspension and oil dispersion images.\nThe mean error of gas/oil volume estimation was used as a\nperformance criterion due to the fact that the main goal of\nthe applications driving the research was the bubble volume\nestimation. The method achieved 28 and 13 % of gas and\noil volume estimation errors correspondingly outperforming\nthe OpenCV Circular Hough Transform in both cases and the\nWaldBoost detector in gas volume estimation....
This article presents a new method to evaluate the geometry of dull cutting tools in order to verify the necessity of tool\nre-sharpening and to decrease the tool grinding machine setup time, based on a laser scanning approach. The developed\nmethod consists of the definition of a system architecture and the programming of all the algorithms needed to analyze\nthe data and provide, as output, the cutting angles of the worn tool. These angles are usually difficult to be measured\nand are needed to set up the grinding machine. The main challenges that have been dealt with in this application are\nrelated to the treatment of data acquired by the system�s cameras, which must be specific for the milling tools, usually\ncharacterized by the presence of undercuts and sharp edges. Starting from the architecture of the system, an industrial\nproduct has been designed, with the support of a grinding machine manufacturer. The basic idea has been to develop a\nlow-cost system that could be integrated on a tool sharpening machine and interfaced with its numeric control. The article\nreports the developed algorithms and an example of application...
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