Computationally adaptive occlusion aware hand landmark estimation

An electronic device, comprising:

• memory storing one or more computer programs;
• and
• one or more processors communicatively coupled to the memory,
• wherein the one or more computer programs include computer-executable instructions that, when executed by the one or more processors, cause the electronic device to:
• generate an initial coarse estimation of at least one landmark point of a body part of a subject using a light-weight deep neural network,
• determine at least one occluded region of the body part based on the generated initial coarse estimation of the at least one landmark points using a segmentation mask,
• estimate an occlusion probability for the at least one landmark point in the at least one occluded region and the generated initial coarse estimation,
• determine a correction factor for applying on the generated initial coarse estimation as a measure of the estimated occlusion probability, and
• select a pre-defined number of neural networks by applying the correction factor, for processing the at least one occluded region and the generated initial coarse estimation to generate final estimation of the at least one landmark point.

One or more non-transitory computer-readable storage media storing one or more computer programs including computer-executable instructions that, when executed by one or more processors of an electronic device, cause the electronic device to perform operations for estimating at least one landmark point of a body part of a subject, the operations comprising:

• generating, by the electronic device, an initial coarse estimation of the at least one landmark point of the body part using a light-weight deep neural network;
• determining, by the electronic device, at least one occluded region of the body part based on the generated initial coarse estimation of the at least one landmark point using a segmentation mask;
• estimating, by the electronic device, an occlusion probability for the at least one landmark point in the at least one occluded region and the generated initial coarse estimation;
• determining, by the electronic device, a correction factor for applying on the generated initial coarse estimation as a measure of the estimated occlusion probability;
• and
• selecting, by the electronic device, a pre-defined number of neural networks by applying the determined correction factor, for processing the at least one occluded region and the generated initial coarse estimation to generate final estimation of the at least one landmark point.