Portal de Periódicos da CAPES

DeepPose: Human Pose Estimation via Deep Neural Networks

2014; Linguagem: Inglês

10.1109/cvpr.2014.214

Alexander Toshev, Christian Szegedy,

Hand Gesture Recognition Systems

We propose a method for human pose estimation based on Deep Neural Networks (DNNs). The pose estimation is formulated as a DNN-based regression problem towards body joints. We present a cascade of such DNN regres- sors which results in high precision pose estimates. The approach has the advantage of reasoning about pose in a holistic fashion and has a simple but yet powerful formula- tion which capitalizes on recent advances in Deep Learn- ing. We present a detailed empirical analysis with state-of- art or better performance on four academic benchmarks of diverse real-world images.