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This paper demonstrates how 3D skeletal reconstruction can be performed by using a pose-sensitive embedding technique applied to multi-view video recordings. We apply our approach to challenging low-resolution video sequences. Usually skeletal reconstruction can be only achieved with many calibrated high-resolution cameras, and only blob detection can be achieved with such low-resolution imagery. We show that with this embedding technique (a metric learning technique using a deep convolutional architecture), we achieve very good 3D skeletal reconstruction on low-resolution outdoor scenes with many challenges.