Obesity Detrimental to Women’s Health

Obesity is the detrimental to overall health and physical performance. Excess amount of body fat is linked to several diseases including type 2 diabetes mellitus, hypertension, hyperlipidemia, cardiovascular diseases and certain type of cancers, and they increase the morbidity and mortality. The mortality rate increases by 50% to 100% when the body mass index (BMI) is equal to or greater than 30Kg.m-2. Most of the women after 30‘s suffered from abdominal obesity or disproportion in hip and waist ratio. It appears to serve as platform for variety of clinical health problems, in addition to greater risk of serious illness. It poses other mechanical limitation that limit performance of daily activities. As individual ages, they may lose the ability to regulate energy intake based on physiologic cues, leading to overeating and weight gain. High caloric food with low in nutrients density and sedentary life style are two major causes of obesity. Several methods are used to determine a person‘s ideal body weight; however in many cases especially for athletes, ideal body weight may be unrealistic. Thus, it is better to focus on a healthy body weight rather than ideal body weight. Healthy body weight is different for each individual, athlete or non athlete, and is one that is relative to a person‘s overall health profile. Prevention of weight gain would likely to decrease chronic disease, improve quality of life and decrease health care cost. So, weight management is required by an every individual by increasing the physical activity every day with proper diet

Recycle-GAN: Unsupervised Video Retargeting

We introduce a data-driven approach for unsupervised video retargeting that translates content from one domain to another while preserving the style native to a domain, i.e., if contents of John Oliver's speech were to be transferred to Stephen Colbert, then the generated content/speech should be in Stephen Colbert's style. Our approach combines both spatial and temporal information along with adversarial losses for content translation and style preservation. In this work, we first study the advantages of using spatiotemporal constraints over spatial constraints for effective retargeting. We then demonstrate the proposed approach for the problems where information in both space and time matters such as face-to-face translation, flower-to-flower, wind and cloud synthesis, sunrise and sunset.Comment: ECCV 2018; Please refer to project webpage for videos - http://www.cs.cmu.edu/~aayushb/Recycle-GA

AUTO3D: Novel view synthesis through unsupervisely learned variational viewpoint and global 3D representation

This paper targets on learning-based novel view synthesis from a single or limited 2D images without the pose supervision. In the viewer-centered coordinates, we construct an end-to-end trainable conditional variational framework to disentangle the unsupervisely learned relative-pose/rotation and implicit global 3D representation (shape, texture and the origin of viewer-centered coordinates, etc.). The global appearance of the 3D object is given by several appearance-describing images taken from any number of viewpoints. Our spatial correlation module extracts a global 3D representation from the appearance-describing images in a permutation invariant manner. Our system can achieve implicitly 3D understanding without explicitly 3D reconstruction. With an unsupervisely learned viewer-centered relative-pose/rotation code, the decoder can hallucinate the novel view continuously by sampling the relative-pose in a prior distribution. In various applications, we demonstrate that our model can achieve comparable or even better results than pose/3D model-supervised learning-based novel view synthesis (NVS) methods with any number of input views.Comment: ECCV 202

Esquisse: Using 3D Models Staging to Facilitate the Creation of Vector-based Trace Figures

https://youtu.be/X2UdHXrvUg0International audienceTrace figures are contour drawings of people and objects that capture the essence of scenes without the visual noise of photos or other visual representations. Their focus and clarity make them ideal representations to illustrate designs or interaction techniques. In practice, creating those figures is a tedious task requiring advanced skills, even when creating the figures by tracing outlines based on photos. To mediate the process of creating trace figures, we introduce the open-source tool Esquisse. Informed by our taxonomy of 124 trace figures, Esquisse provides an innovative 3D model staging workflow, with specific interaction techniques that facilitate 3D staging through kinematic manipulation, anchor points and posture tracking. Our rendering algorithm (including stroboscopic rendering effects) creates vector-based trace figures of 3D scenes. We validated Esquisse with an experiment where participants created trace figures illustrating interaction techniques, and results show that participants quickly managed to use and appropriate the tool