Detección de personas basada en HOG y SVM

El presente proyecto se centra en proteger a los peatones de las vías urbanas o de una fábrica donde conviven con robots móviles, pues son los mayores afectados en los acci- dentes producidos en estos entornos. El objetivo es diseñar un algoritmo basado en visión monocular capaz de detectar a los usuarios de forma rápida y precisa de tal forma que se tenga constancia en todo momento de los peatones que se encuentran delante del vehículo.

Efficient HOG human detection

While Histograms of Oriented Gradients (HOG) plus Support Vector Machine (SVM) (HOG+SVM) is the most successful human detection algorithm, it is time-consuming. This paper proposes two ways to deal with this problem. One way is to reuse the features in blocks to construct the HOG features for intersecting detection windows. Another way is to utilize sub-cell based interpolation to efficiently compute the HOG features for each block. The combination of the two ways results in significant increase in detecting humans-more than five times better. To evaluate the proposed method, we have established a top-view human database. Experimental results on the top-view database and the well-known INRIA data set have demonstrated the effectiveness and efficiency of the proposed method. (C) 2010 Elsevier B.V. All rights reserved.

FPGA Soft-core Processors, Compiler and Hardware Optimizations validated using HOG

There is demand for an easily programmable, high performance image processing platform based on FPGAs. In previous work, a novel, high performance processor - IPPro was developed and a Histogram of Orientated Gradients (HOG) algorithm study undertaken on a Xilinx Zynq platform. Here, we identify and explore a number of mapping strategies to improve processing efficiency for soft-cores and a number of options for creation of a division coprocessor. This is demonstrated for the revised high definition HOG implementation on a Zynq platform, resulting in a performance of 328 fps which represents a 146% speed improvement over the original realization and a tenfold reduction in energy.

Note from the Port Dalhousie and Thorold Railway to Mrs. E. Parnell with prices for digging a well, moving a hog pen and repairing a fence

Note from the Port Dalhousie and Thorold Railway to Mrs. E. Parnell with prices for digging a well, moving a hog pen and repairing a fence, n.d.

Benchmark Evaluation of HOG Descriptors as Features for Classification of Traffic Signs

The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.

ChIP-seq reveals a role for CrzA in the Aspergillus fumigatus high-osmolarity glycerol response (HOG) signalling pathway

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variation of Environmental Regulation Stringency Among the Top Ten U.S. Hog Producing States

The U.S. hog industry, once primarily made up of small owner-operated crop-hog farms, has become dominated by large specialized operations characterized by low costs and improved technologies in livestock management. Such changes have triggered concerns over the dangers large Hog Feeding Operations (HFOs) are likely to pose to the environment. In 2007, the top ten states accounted for more than 85 percent of total U.S. hog production (Iowa (IA), North Carolina (NC), Minnesota (MN), Illinois (IL), Nebraska (NE), Indiana (IN), Missouri (MO), Oklahoma (OK), Ohio (OH), and Kansas (KS)). With such domination on production, these states are often the subject of environmental debate relating to hog production. When farmers are required to incorporate environmental measures in hog production, their costs of production increase. Metcalfe (2001) found that small HFOs have found it difficult to cope with such costs and many have exited the industry, while large operations have not been affected at the same level. Due to the variation of environmental regulations among states, other operations moved to states with lax regulations (e.g. NC prior to the late 1990s). Such regulations appear to have played a major role in shaping the structure of the hog industry.

Evaluation of LBP and HOG descriptors for clothing attribute description

[EN]In this work an experimental study about the capability of the LBP, HOG descriptors and color for clothing attribute classification is presented. Two different variants of the LBP descriptor are considered, the original LBP and the uniform LBP. Two classifiers, Linear SVM and Random Forest, have been included in the comparison because they have been frequently used in clothing attributes classification. The experiments are carried out with a public available dataset, the clothing attribute dataset, that has 26 attributes in total. The obtained accuracies are over 75% in most cases, reaching 80% for the necktie or sleeve length attributes.

Responding to Price Signals in Communal Agriculture: Shaker Hog Production, 1788-1850

Isolated Shaker communal farms stressed self-sufficiency as an ideal but carefully chose which goods to buy and sell in external markets and which to produce and consume themselves. We use records of hog slaughter weights to investigate the extent to which the Shakers incorporated market-based price information in determining production levels of a consumption good which they did not sell in external markets: pork. Granger causality tests indicate that Shaker pork production decisions were influenced as hypothesized, strongly by corn prices and weakly by pork prices. We infer that attention to opportunity costs of goods that they produced and consumed themselves was a likely factor aiding the longevity of Shaker communal societies.

Seawater carbonate chemistry in Hog reef and calcification rate in the Bermuda reef community, 2010

Despite the potential impact of ocean acidification on ecosystems such as coral reefs, surprisingly, there is very limited field data on the relationships between calcification and seawater carbonate chemistry. In this study, contemporaneous in situ datasets of seawater carbonate chemistry and calcification rates from the high-latitude coral reef of Bermuda over annual timescales provide a framework for investigating the present and future potential impact of rising carbon dioxide (CO2) levels and ocean acidification on coral reef ecosystems in their natural environment. A strong correlation was found between the in situ rates of calcification for the major framework building coral species Diploria labyrinthiformis and the seasonal variability of [CO32-] and aragonite saturation state omega aragonite, rather than other environmental factors such as light and temperature. These field observations provide sufficient data to hypothesize that there is a seasonal "Carbonate Chemistry Coral Reef Ecosystem Feedback" (CREF hypothesis) between the primary components of the reef ecosystem (i.e., scleractinian hard corals and macroalgae) and seawater carbonate chemistry. In early summer, strong net autotrophy from benthic components of the reef system enhance [CO32-] and omega aragonite conditions, and rates of coral calcification due to the photosynthetic uptake of CO2. In late summer, rates of coral calcification are suppressed by release of CO2 from reef metabolism during a period of strong net heterotrophy. It is likely that this seasonal CREF mechanism is present in other tropical reefs although attenuated compared to high-latitude reefs such as Bermuda. Due to lower annual mean surface seawater [CO32-] and omega aragonite in Bermuda compared to tropical regions, we anticipate that Bermuda corals will experience seasonal periods of zero net calcification within the next decade at [CO32-] and omega aragonite thresholds of ~184 micro moles kg-1 and 2.65. However, net autotrophy of the reef during winter and spring (as part of the CREF hypothesis) may delay the onset of zero NEC or decalcification going forward by enhancing [CO32-] and omega aragonite. The Bermuda coral reef is one of the first responders to the negative impacts of ocean acidification, and we estimate that calcification rates for D. labyrinthiformis have declined by >50% compared to pre-industrial times.

HOG-Like gradient-based descriptor for visual vehicle detection

One of the main challenges for intelligent vehicles is the capability of detecting other vehicles in their environment, which constitute the main source of accidents. Specifically, many methods have been proposed in the literature for video-based vehicle detection. Most of them perform supervised classification using some appearance-related feature, in particular, symmetry has been extensively utilized. However, an in-depth analysis of the classification power of this feature is missing. As a first contribution of this paper, a thorough study of the classification performance of symmetry is presented within a Bayesian decision framework. This study reveals that the performance of symmetry-based classification is very limited. Therefore, as a second contribution, a new gradient-based descriptor is proposed for vehicle detection. This descriptor exploits the known rectangular structure of vehicle rears within a Histogram of Gradients (HOG)-based framework. Experiments show that the proposed descriptor outperforms largely symmetry as a feature for vehicle verification, achieving classification rates over 90%.