Recovering 6D Object Pose: A Review and Multi-modal Analysis

A large number of studies analyse object detection and pose estimation at visual level in 2D, discussing the effects of challenges such as occlusion, clutter, texture, etc., on the performances of the methods, which work in the context of RGB modality. Interpreting the depth data, the study in this paper presents thorough multi-modal analyses. It discusses the above-mentioned challenges for full 6D object pose estimation in RGB-D images comparing the performances of several 6D detectors in order to answer the following questions: What is the current position of the computer vision community for maintaining "automation" in robotic manipulation? What next steps should the community take for improving "autonomy" in robotics while handling objects? Our findings include: (i) reasonably accurate results are obtained on textured-objects at varying viewpoints with cluttered backgrounds. (ii) Heavy existence of occlusion and clutter severely affects the detectors, and similar-looking distractors is the biggest challenge in recovering instances' 6D. (iii) Template-based methods and random forest-based learning algorithms underlie object detection and 6D pose estimation. Recent paradigm is to learn deep discriminative feature representations and to adopt CNNs taking RGB images as input. (iv) Depending on the availability of large-scale 6D annotated depth datasets, feature representations can be learnt on these datasets, and then the learnt representations can be customized for the 6D problem

Declining trends in conception rates in recent birth cohorts of native Danish women: a possible role of deteriorating male reproductive health

Recent findings of poor semen quality among at least 20% of normal young men in Denmark prompted us to use unique Danish registers on births and induced abortions to evaluate a possible effect of the poor male fecundity on pregnancy rates among their presumed partners – the younger cohorts of women. We have analysed data from the Danish birth and abortion registries as well as the Danish registry for assisted reproduction (ART) and defined a total natural conception rate (TNCR), which is equal to fertility rate plus induced abortion rate minus ART conception rate. A unique personal identification number allowed the linkage of these databases. Our database included 706 270 native Danish women born between 1960 and 1980. We used projections to estimate the fertility of the later cohorts of women who had not yet finished their reproduction. We found that younger cohorts had progressively lower TNCR and that in terms of their total fertility rate, the declining TNCR is compensated by an increasing use of ART. Our hypothesis of an ongoing birth cohort-related decline in fecundity was also supported by our finding of increasing and substantial use of ART in the management of infertility of relatively young couples in the later cohorts. Furthermore, the lower rates of induced abortion among the younger birth cohorts, often viewed as a success of health education programs, may not be fully explained by improved use of contraception. It seems more likely that decreased fecundity because of widespread poor semen quality among younger cohorts of otherwise normal men may explain some of the observed decline in conception rates. This may imply increasing reproductive health problems and lower fertility in the future, which is difficult to reverse in the short term. The current and projected widespread use of ART in Denmark may be a sign of such an emerging public health problem

Prevalence of lameness and claw lesions during different stages in the reproductive cycle of sows and the impact on reproduction results

Lameness in sows is an emerging disease condition with major effects on animal welfare and economics. Yet the direct impact on reproduction results remains unclear. The present field study investigated the impact of lameness and claw lesions throughout the reproductive cycle on (re)production results of sows. In five farms, a total of 491 group-housed sows were followed up for a period of one reproductive cycle. Sows were assessed for lameness every time they were moved to another area in the farm. Claw lesions were scored at the beginning and at the end of the cycle. Reproduction results included the number of live-born piglets, stillborn piglets, mummified fetuses and crushed piglets, weaning-to-oestrus interval and the presence of sows not showing oestrus post weaning, returning to service and aborting. Sows that left the group were recorded and the reason was noted. A mean prevalence of lameness of 5.9% was found, although it depended on the time in the productive cycle. The highest percentage of lame sows (8.1%) was found when sows were moved from the post-weaning to the gestation stable. No significant associations were found between lameness and reproduction parameters with the exception of the effect on mummified foetuses. Wall cracks, white line lesions, heel lesions and skin lesions did have an effect on farrowing performance. Of all sows, 22% left the group throughout the study, and almost half of these sows were removed from the farm. Lameness was the second most important reason for culling. Sows culled because of lameness were significantly younger compared with sows culled for other reasons (parity: 2.6 +/- 1.3 v. 4.0 +/- 1.8). In conclusion, the present results indicate that lameness mainly affects farm productivity indirectly through its effect on sow longevity whereas claw lesions directly affect some reproductive parameters. The high percentage of lame sows in the insemination stable indicate that risk factor studies should not only focus on the gestation stable, but also on housing conditions in the insemination stable

Bio-nanotechnology application in wastewater treatment

The nanoparticles have received high interest in the field of medicine and water purification, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modification of nanoparticles and their properties were also discussed

GSMN-TB : a web-based genome-scale network model of Mycobacterium tuberculosis metabolism

An impediment to the rational development of novel drugs against tuberculosis (TB) is a general paucity of knowledge concerning the metabolism of Mycobacterium tuberculosis, particularly during infection. Constraint-based modeling provides a novel approach to investigating microbial metabolism but has not yet been applied to genome-scale modeling of M. tuberculosis. Results GSMN-TB, a genome-scale metabolic model of M. tuberculosis, was constructed, consisting of 849 unique reactions and 739 metabolites, and involving 726 genes. The model was calibrated by growing Mycobacterium bovis bacille Calmette Guérin in continuous culture and steady-state growth parameters were measured. Flux balance analysis was used to calculate substrate consumption rates, which were shown to correspond closely to experimentally determined values. Predictions of gene essentiality were also made by flux balance analysis simulation and were compared with global mutagenesis data for M. tuberculosis grown in vitro. A prediction accuracy of 78% was achieved. Known drug targets were predicted to be essential by the model. The model demonstrated a potential role for the enzyme isocitrate lyase during the slow growth of mycobacteria, and this hypothesis was experimentally verified. An interactive web-based version of the model is available. Conclusion The GSMN-TB model successfully simulated many of the growth properties of M. tuberculosis. The model provides a means to examine the metabolic flexibility of bacteria and predict the phenotype of mutants, and it highlights previously unexplored features of M. tuberculosis metabolism

Towards Viewpoint Invariant 3D Human Pose Estimation

We propose a viewpoint invariant model for 3D human pose estimation from a single depth image. To achieve this, our discriminative model embeds local regions into a learned viewpoint invariant feature space. Formulated as a multi-task learning problem, our model is able to selectively predict partial poses in the presence of noise and occlusion. Our approach leverages a convolutional and recurrent network architecture with a top-down error feedback mechanism to self-correct previous pose estimates in an end-to-end manner. We evaluate our model on a previously published depth dataset and a newly collected human pose dataset containing 100 K annotated depth images from extreme viewpoints. Experiments show that our model achieves competitive performance on frontal views while achieving state-of-the-art performance on alternate viewpoints

Data sharing: not as simple as it seems

In recent years there has been a major change on the part of funders, particularly in North America, so that data sharing is now considered to be the norm rather than the exception. We believe that data sharing is a good idea. However, we also believe that it is inappropriate to prescribe exactly when or how researchers should preserve and share data, since these issues are highly specific to each study, the nature of the data collected, who is requesting it, and what they intend to do with it. The level of ethical concern will vary according to the nature of the information, and the way in which it is collected - analyses of anonymised hospital admission records may carry a quite different ethical burden than analyses of potentially identifiable health information collected directly from the study participants. It is striking that most discussions about data sharing focus almost exclusively on issues of ownership (by the researchers or the funders) and efficiency (on the part of the funders). There is usually little discussion of the ethical issues involved in data sharing, and its implications for the study participants. Obtaining prior informed consent from the participants does not solve this problem, unless the informed consent process makes it completely clear what is being proposed, in which case most study participants would not agree. Thus, the undoubted benefits of data sharing does not remove the obligations and responsibilities that the original investigators hold for the people they invited to participate in the study