dataset_info = dict( dataset_name='h36m', paper_info=dict( author='Ionescu, Catalin and Papava, Dragos and ' 'Olaru, Vlad and Sminchisescu, Cristian', title='Human3.6M: Large Scale Datasets and Predictive ' 'Methods for 3D Human Sensing in Natural Environments', container='IEEE Transactions on Pattern Analysis and ' 'Machine Intelligence', year='2014', homepage='http://vision.imar.ro/human3.6m/description.php', ), keypoint_info={ 0: dict(name='root', id=0, color=[51, 153, 255], type='lower', swap=''), 1: dict( name='right_hip', id=1, color=[255, 128, 0], type='lower', swap='left_hip'), 2: dict( name='right_knee', id=2, color=[255, 128, 0], type='lower', swap='left_knee'), 3: dict( name='right_foot', id=3, color=[255, 128, 0], type='lower', swap='left_foot'), 4: dict( name='left_hip', id=4, color=[0, 255, 0], type='lower', swap='right_hip'), 5: dict( name='left_knee', id=5, color=[0, 255, 0], type='lower', swap='right_knee'), 6: dict( name='left_foot', id=6, color=[0, 255, 0], type='lower', swap='right_foot'), 7: dict(name='spine', id=7, color=[51, 153, 255], type='upper', swap=''), 8: dict(name='thorax', id=8, color=[51, 153, 255], type='upper', swap=''), 9: dict( name='neck_base', id=9, color=[51, 153, 255], type='upper', swap=''), 10: dict(name='head', id=10, color=[51, 153, 255], type='upper', swap=''), 11: dict( name='left_shoulder', id=11, color=[0, 255, 0], type='upper', swap='right_shoulder'), 12: dict( name='left_elbow', id=12, color=[0, 255, 0], type='upper', swap='right_elbow'), 13: dict( name='left_wrist', id=13, color=[0, 255, 0], type='upper', swap='right_wrist'), 14: dict( name='right_shoulder', id=14, color=[255, 128, 0], type='upper', swap='left_shoulder'), 15: dict( name='right_elbow', id=15, color=[255, 128, 0], type='upper', swap='left_elbow'), 16: dict( name='right_wrist', id=16, color=[255, 128, 0], type='upper', swap='left_wrist') }, skeleton_info={ 0: dict(link=('root', 'left_hip'), id=0, color=[0, 255, 0]), 1: dict(link=('left_hip', 'left_knee'), id=1, color=[0, 255, 0]), 2: dict(link=('left_knee', 'left_foot'), id=2, color=[0, 255, 0]), 3: dict(link=('root', 'right_hip'), id=3, color=[255, 128, 0]), 4: dict(link=('right_hip', 'right_knee'), id=4, color=[255, 128, 0]), 5: dict(link=('right_knee', 'right_foot'), id=5, color=[255, 128, 0]), 6: dict(link=('root', 'spine'), id=6, color=[51, 153, 255]), 7: dict(link=('spine', 'thorax'), id=7, color=[51, 153, 255]), 8: dict(link=('thorax', 'neck_base'), id=8, color=[51, 153, 255]), 9: dict(link=('neck_base', 'head'), id=9, color=[51, 153, 255]), 10: dict(link=('thorax', 'left_shoulder'), id=10, color=[0, 255, 0]), 11: dict(link=('left_shoulder', 'left_elbow'), id=11, color=[0, 255, 0]), 12: dict(link=('left_elbow', 'left_wrist'), id=12, color=[0, 255, 0]), 13: dict(link=('thorax', 'right_shoulder'), id=13, color=[255, 128, 0]), 14: dict( link=('right_shoulder', 'right_elbow'), id=14, color=[255, 128, 0]), 15: dict(link=('right_elbow', 'right_wrist'), id=15, color=[255, 128, 0]) }, joint_weights=[1.] * 17, sigmas=[], stats_info=dict(bbox_center=(528., 427.), bbox_scale=400.))