Patent ID: 8345984

Claim:
A computer implemented method to automatically recognize human actions from one or more video frames, comprising: performing 3D convolutions to capture motion information encoded in multiple adjacent frames and extracting features from spatial and temporal dimensions therefrom; generating multiple channels of information from the video frames, combining information from all channels to obtain a feature representation for a three dimensional convolution neural network (3D CNN) model including determining a value v at position (x, y, z) on a j th feature map in an i th layer of the 3D CNN as: v ij xyz = tanh ⁡ ( b ij + ∑ m ⁢ ∑ p = 0 P i - 1 ⁢ ∑ q = 0 Q i - 1 ⁢ ∑ r = 0 R i - 1 ⁢ w ijm pqr ⁢ v ( i - 1 ) ⁢ m ( x + p ) ⁢ ( y + q ) ⁢ ( z + r ) ) , where tanh(•) is the hyperbolic tangent function, P i and Q i are height and width of a 3D kernel, R i is the size of the 3D kernel along a temporal dimension, w ijm pqr is the (p, q, r) th value of the kernel connected to the m th feature map in a previous layer, and b ij is a feature map bias; and applying the 3D CNN model to recognize human actions.