Method for identifying a hand pose in a vehicle

A computerized method, comprising:

• extracting a hand image of a hand in a vehicle image of a vehicle using a single point associated with the hand, wherein a size of the extracted hand image is fixed and predetermined, and wherein the single point is at a fixed position within the extracted hand image of a fixed and predetermined size;
• obtaining a plurality of contextual images of the hand image based on the single point, wherein each of the plurality of contextual images is obtained by
• selecting the single point at the fixed position in the hand image;
• and
• cropping the hand image to a corresponding predefined size based on the single point as a center point;
• processing each of the plurality of contextual images using a predefined number of layers of a neural network to obtain a plurality of contextual features associated with the hand image;
• identifying, using a classifier model, a hand pose associated with the hand based on the plurality of contextual features;
• and
• performing, by an event performing system, an event corresponding to the identified hand pose.

A system, comprising:

• a processor;
• and
• a non-transitory memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, cause the processor to:
• extract a hand image of a hand in a vehicle image of a vehicle using a single point associated with the hand, wherein a size of the extracted hand image is fixed and predetermined, and wherein the single point is at a fixed position within the extracted hand image of a fixed and predetermined size;
• obtain a plurality of contextual images of the hand image based on the single point, wherein each of the plurality of contextual images is obtained by
• selecting the single point at the fixed position in the hand image;
• and
• cropping the hand image to a corresponding predefined size based on the single point as a center point;
• process each of the plurality of contextual images using a predefined number of layers of a neural network to obtain a plurality of contextual features associated with the hand image;
• and
• identify, using a classifier model, a hand pose associated with the hand based on the plurality of contextual features.