Human Pose Estimation using Global and Local Normalization

In this paper, we address the problem of estimating the positions of human joints, i.e., articulated pose estimation. Recent state-of-the-art solutions model two key issues, joint detection and spatial configuration refinement, together using convolutional neural networks. Our work mainly focuses on spatial configuration refinement by reducing variations of human poses statistically, which is motivated by the observation that the scattered distribution of the relative locations of joints e.g., the left wrist is distributed nearly uniformly in a circular area around the left shoulder) makes the learning of convolutional spatial models hard. We present a two-stage normalization scheme, human body normalization and limb normalization, to make the distribution of the relative joint locations compact, resulting in easier learning of convolutional spatial models and more accurate pose estimation. In addition, our empirical results show that incorporating multi-scale supervision and multi-scale fusion into the joint detection network is beneficial. Experiment results demonstrate that our method consistently outperforms state-of-the-art methods on the benchmarks.Comment: ICCV201

High-Tech Service Platform Ecosystem Evolution: A Simulation Analysis using Lotka-Volterra Model

Technical service platform exerts a strong effect on supporting the innovation of the high-tech industry as a critical constituent of the modern service industry, and it can effectively enhance the development potential of technological innovation, but the degree of separation from technical service chain to high-tech industry chain is currently high. To explore how to improve the utilization efficiency of scientific and technological resources and facilitate the sustainable development of the high-tech industry by relying on technical service platform,a high-tech service platform was constructed by using Lotka-Volterra (L-V) model on the basis of ecosystem theory, the evolution path and stability conditions of high-tech service platform were analyzed followed by numerical simulation by Matlab computing. Results show that the development of hightech service platform follows the evolution path of "bilateral platform → core platform → platform ecosystem"; population evolution pattern in high-tech service platform ecosystem is decided by interdependence coefficient between populations; populations inside high-tech service platform ecosystem generate natural selection and synergistic effect and realize ecological balance among populations through evolution. Evolution of high-tech service platform system in this study provides a new theoretical framework for effective fusion and collaboration of science and technology service and industry, which is significant for elevating scientific and technological innovation level and improving technical service system construction