Region-Based Image Retrieval Revisited

Region-based image retrieval (RBIR) technique is revisited. In early attempts at RBIR in the late 90s, researchers found many ways to specify region-based queries and spatial relationships; however, the way to characterize the regions, such as by using color histograms, were very poor at that time. Here, we revisit RBIR by incorporating semantic specification of objects and intuitive specification of spatial relationships. Our contributions are the following. First, to support multiple aspects of semantic object specification (category, instance, and attribute), we propose a multitask CNN feature that allows us to use deep learning technique and to jointly handle multi-aspect object specification. Second, to help users specify spatial relationships among objects in an intuitive way, we propose recommendation techniques of spatial relationships. In particular, by mining the search results, a system can recommend feasible spatial relationships among the objects. The system also can recommend likely spatial relationships by assigned object category names based on language prior. Moreover, object-level inverted indexing supports very fast shortlist generation, and re-ranking based on spatial constraints provides users with instant RBIR experiences.Comment: To appear in ACM Multimedia 2017 (Oral

Comparison of fusion methods for thermo-visual surveillance tracking

In this paper, we evaluate the appearance tracking performance of multiple fusion schemes that combine information from standard CCTV and thermal infrared spectrum video for the tracking of surveillance objects, such as people, faces, bicycles and vehicles. We show results on numerous real world multimodal surveillance sequences, tracking challenging objects whose appearance changes rapidly. Based on these results we can determine the most promising fusion scheme

PanDA: Panoptic Data Augmentation

The recently proposed panoptic segmentation task presents a significant challenge of image understanding with computer vision by unifying semantic segmentation and instance segmentation tasks. In this paper we present an efficient and novel panoptic data augmentation (PanDA) method which operates exclusively in pixel space, requires no additional data or training, and is computationally cheap to implement. By retraining original state-of-the-art models on PanDA augmented datasets generated with a single frozen set of parameters, we show robust performance gains in panoptic segmentation, instance segmentation, as well as detection across models, backbones, dataset domains, and scales. Finally, the effectiveness of unrealistic-looking training images synthesized by PanDA suggest that one should rethink the need for image realism for efficient data augmentation

Pedestrian Traffic Fatalities by State: 2016 Preliminary Data

The present study, based on preliminary data from all states and the District of Columbia (DC) for the first six months of 2016, found an increase of seven percent in the reported number of fatalities compared with the first six months of 2015. More than twice as many states had increases (34) than had decreases (15 plus DC) compared with 2015.After adjusting for anticipated underreporting in the preliminary state data, GHSA estimates the number of pedestrians killed in 2016 increased by 11 percent compared with 2015. This was the largest annual increase in both the number and percentage of pedestrian fatalities in the 40 years that national records have been kept, with the second largest increase occurring in 2015. In addition, pedestrian deaths as a percent of total motor vehicle crash deaths have increased steadily, from 11 percent in 2006 to 15 percent in 2015.The number of nationwide pedestrian fatalities for all of 2016 was estimated based on preliminary data provided by State Highway Safety Offices (SHSOs) for the first six months of 2016, taking into account historic data regarding the relative proportions of pedestrian fatalities that occurred in the first and second halves of the year. About 6,000 pedestrian fatalities are estimated to have occurred in 2016, which could make 2016 the first year in more than two decades with more than 6,000 pedestrain deaths

Solar Neutrinos

The study of solar neutrinos has given since ever a fundamental contribution both to astroparticle and to elementary particle physics, offering an ideal test of solar models and offering at the same time relevant indications on the fundamental interactions among particles. After reviewing the striking results of the last two decades, which were determinant to solve the long standing solar neutrino puzzle and refine the Standard Solar Model, we focus our attention on the more recent results in this field and on the experiments presently running or planned for the near future. The main focus at the moment is to improve the knowledge of the mass and mixing pattern and especially to study in detail the lowest energy part of the spectrum, which represents most of solar neutrino spectrum but is still a partially unexplored realm. We discuss this research project and the way in which present and future experiments could contribute to make the theoretical framemork more complete and stable, understanding the origin of some "anomalies" that seem to emerge from the data and contributing to answer some present questions, like the exact mechanism of the vacuum to matter transition and the solution of the so called solar metallicity problem.Comment: 51 pages, to be published in Special Issue on Neutrino Physics, Advances in High Energy Physics Hindawi Publishing Corporation 201

What makes for effective detection proposals?

Current top performing object detectors employ detection proposals to guide the search for objects, thereby avoiding exhaustive sliding window search across images. Despite the popularity and widespread use of detection proposals, it is unclear which trade-offs are made when using them during object detection. We provide an in-depth analysis of twelve proposal methods along with four baselines regarding proposal repeatability, ground truth annotation recall on PASCAL, ImageNet, and MS COCO, and their impact on DPM, R-CNN, and Fast R-CNN detection performance. Our analysis shows that for object detection improving proposal localisation accuracy is as important as improving recall. We introduce a novel metric, the average recall (AR), which rewards both high recall and good localisation and correlates surprisingly well with detection performance. Our findings show common strengths and weaknesses of existing methods, and provide insights and metrics for selecting and tuning proposal methods.Comment: TPAMI final version, duplicate proposals removed in experiment

Space flight research relevant to health, physical education, and recreation: With particular reference to Skylab's life science experiments

Data collected in the Skylab program relating to physiological stresses is presented. Included are routine blood measures used in clinical medicine as research type endocrine analyses to investigate the metabolic/endocrine responses to weightlessness. The daily routine of physical exercise, coupled with appropriate dietary intake, sleep, work, and recreation periods were considered essential in maintaining the crew's health and well being

Prevalence of asymptomatic malaria and bed net ownership and use in Bhutan, 2013: a country earmarked for malaria elimination

BACKGROUND With dwindling malaria cases in Bhutan in recent years, the government of Bhutan has made plans for malaria elimination by 2016. This study aimed to determine coverage, use and ownership of LLINs, as well as the prevalence of asymptomatic malaria at a single time-point, in four sub-districts of Bhutan. METHODS A cross-sectional study was carried out in August 2013. Structured questionnaires were administered to a single respondent in each household (HH) in four sub-districts. Four members from 25 HH, randomly selected from each sub-district, were tested using rapid diagnostic tests (RDT) for asymptomatic Plasmodium falciparum and Plasmodium vivax infection. Multivariable logistic regression models were used to identify factors associated with LLIN use and maintenance. RESULTS All blood samples from 380 participants tested negative for Plasmodium infections. A total of 1,223 HH (92.5% of total HH) were surveyed for LLIN coverage and use. Coverage of LLINs was 99.0% (1,203/1,223 HH). Factors associated with decreased odds of sleeping under a LLIN included: washing LLINs nine months compared to washing LLINs every six months; HH in the least poor compared to the most poor socio-economic quintile; a HH income of Nu 5,001-10,000 (US$1 = Nu 59.55), and Nu >10,000, compared to HH with income of <Nu 1,500; HH located one to three hours walking distance to a health centre compared to being located closer to a health centre; a reported lack of knowledge as to what to do in event of LLINs being torn; and keeping LLINs in a box compared to keeping them hanging in the place of use. Factors associated with use of LLINs for purposes other than the intended use included: income group Nu 1,501-3,000 and HH located one to three hours walking distance from a health centre. CONCLUSIONS There was high coverage of LLINs in the study area with regular use of LLINs throughout the year. LLIN use for purposes other than malaria prevention was low. With high coverage and regular use of LLINs, and a zero prevalence of malaria infection found in historically high-risk communities during the peak malaria season, it appears Bhutan is on course to achieve malaria elimination.We acknowledge Queensland Infectious Disease Unit for providing funds to carry out this study