A Survey on Joint Object Detection and Pose Estimation using Monocular Vision

In this survey we present a complete landscape of joint object detection and pose estimation methods that use monocular vision. Descriptions of traditional approaches that involve descriptors or models and various estimation methods have been provided. These descriptors or models include chordiograms, shape-aware deformable parts model, bag of boundaries, distance transform templates, natural 3D markers and facet features whereas the estimation methods include iterative clustering estimation, probabilistic networks and iterative genetic matching. Hybrid approaches that use handcrafted feature extraction followed by estimation by deep learning methods have been outlined. We have investigated and compared, wherever possible, pure deep learning based approaches (single stage and multi stage) for this problem. Comprehensive details of the various accuracy measures and metrics have been illustrated. For the purpose of giving a clear overview, the characteristics of relevant datasets are discussed. The trends that prevailed from the infancy of this problem until now have also been highlighted.Comment: Accepted at the International Joint Conference on Computer Vision and Pattern Recognition (CCVPR) 201

Comparison of accelerometer measured levels of physical activity and sedentary time between obese and non-obese children and adolescents: a systematic review

Background: Obesity has been hypothesized to be associated with reduced moderate-to-vigorous physical activity (MVPA) and increased sedentary time (ST). It is important to assess whether, and the extent to which, levels of MVPA and ST are suboptimal among children and adolescents with obesity. The primary objective of this study was to examine accelerometer-measured time spent in MVPA and ST of children and adolescents with obesity, compared with MVPA recommendations, and with non-obese peers. Methods: An extensive search was carried out in Medline, Cochrane library, EMBASE, SPORTDiscus, and CINAHL, from 2000 to 2015. Study selection and appraisal: studies with accelerometer-measured MVPA and/or ST (at least 3 days and 6 h/day) in free-living obese children and adolescents (0 to 19 years) were included. Study quality was assessed formally. Meta-analyses were planned for all outcomes but were precluded due to the high levels of heterogeneity across studies. Therefore, narrative syntheses were employed for all the outcomes. Results: Out of 1503 records, 26 studies were eligible (n = 14,739 participants; n = 3523 with obesity); 6/26 studies involved children aged 0 to 9 years and 18/26 involved adolescents aged 10.1 to19 years. In the participants with obesity, the time spent in MVPA was consistently below the recommended 60 min/day and ST was generally high regardless of the participant’s age and gender. Comparison with controls suggested that the time spent in MVPA was significantly lower in children and adolescents with obesity, though differences were relatively small. Levels of MVPA in the obese and non-obese were consistently below recommendations. There were no marked differences in ST between obese and non-obese peers. Conclusions: MVPA in children and adolescents with obesity tends to be well below international recommendations. Substantial effort is likely to be required to achieve the recommended levels of MVPA among obese individuals in obesity treatment interventions

Measurement of the Communication Possibility of Service Requests for Multiservers in Parallel Connection in Cloud Computing Systems

Newly, growing amount of data‐demanding applications arrangement with continuous fluctuating data substances, have been investigated by many researchers recently. In these applications, the underlying data management system must support new types of the space‐time changing that indicates to the paths of the cloud computing system (CCS). The time‐space changing causes change in the dimension of data and, consequently, in the CCS. One of the solutions regarding this case is suggesting an integrated cloud computing system (ICCS). In this effort, we introduce a new ICCS, based on fractional formal operators, taking into account the symmetrical delay in it. This model is useful for higher dimensional data, moving data, and chaos data. Moreover, we employ a fractional differential method to discover the paths (outcomes) of the system by minimizing the cost function. The proposed system delivers a sequence of paths that converge to the optimal path. The theoretical technique is supported by the applications