Multi-Person Pose Estimation with Local Joint-to-Person Associations

Despite of the recent success of neural networks for human pose estimation, current approaches are limited to pose estimation of a single person and cannot handle humans in groups or crowds. In this work, we propose a method that estimates the poses of multiple persons in an image in which a person can be occluded by another person or might be truncated. To this end, we consider multi-person pose estimation as a joint-to-person association problem. We construct a fully connected graph from a set of detected joint candidates in an image and resolve the joint-to-person association and outlier detection using integer linear programming. Since solving joint-to-person association jointly for all persons in an image is an NP-hard problem and even approximations are expensive, we solve the problem locally for each person. On the challenging MPII Human Pose Dataset for multiple persons, our approach achieves the accuracy of a state-of-the-art method, but it is 6,000 to 19,000 times faster.Comment: Accepted to European Conference on Computer Vision (ECCV) Workshops, Crowd Understanding, 201

Зміни міждиферонної та внутрішньодиферонної гетероморфії тканин шкіри за умов впливу наночастинок срібла розміром 20, 30, 70 нм

The study is focused on developing of morphological criteria of biological tissue reactions to metal nanoparticles by detecting changes of tissues heteromorphism interacting with NPs. The study of heteromorphism tissue provides an integrated assessment of functional state of the tissue, allowing objectively evaluate the response of biological tissues in metal nanoparticles. Size-dependent effects of silver nanoparticles were identified, namely depending on the nanoparticles size recovery rate of basement membrane structure differs; the increase of mitotic index of the epidermal basal cells; changes of dermal fibroblasts’s heteromorphism, such as increasing of number of functionally active fibroblasts; and the number of collagen fibers of the dermis. Reactive changes of intradifferon heteromorphism of epidermal basal cells and the dermal fibroblasts was described using quantitative histological methods.Метою дослідження є розробка морфологічних критеріїв оцінки реакцій біологічних тканин на металеві наночастинки методом змін внутрішньо- й міждиферонної гетероморфії тканин, які взаємодіють із наночастинками. Вивчення тканинної гетероморфії забезпечує комплексну оцінку функціо нального стану тканини, дозволяючи об’єктивно оцінити реакцію біологічних тканин при взаємодії з наночастинками металів. За допомогою кількісних гістологічних методик описані реактивні зміни внутрішньодиферонної гетероморфії клітин базального шару епідермісу і фібробластів дерми. Виявлені розмірозалежні ефекти впливу наночастинок срібла

2D Articulated Human Pose Estimation and Retrieval in (Almost) Unconstrained Still Images

Abstract We present a technique for estimating the spatial layout of humans in still images—the position of the head, torso and arms. The theme we explore is that once a person is localized using an upper body detector, the search for their body parts can be considerably simplified using weak constraints on position and appearance arising from that detection. Our approach is capable of estimating upper body pose in highly challenging uncontrolled images, without prior knowledge of background, clothing, lighting, or the location and scale of the person in the image. People are only required to be upright and seen from the front or the back (not side). We evaluate the stages of our approach experimentally using ground truth layout annotation on a variety of challenging material, such as images from the PASCAL VOC 2008 challenge and video frames from TV shows and feature films. We also propose and evaluate techniques for searching a video dataset for people in a specific pose. To this end, we develop three new pose descriptors and compare their clas