Method and apparatus for processing image based on partial images

An apparatus for processing an image, the apparatus comprising:

• a processor;
• and
• a memory configured to store instructions executable by the processor,
• wherein in response to the instructions being executed by the processor, the processor is configured to:
• extract a feature of a current partial processing region of an input image frame by inputting pixel data of the current partial processing region into a convolutional neural network (CNN),
• update a hidden state of a recurrent neural network (RNN) for a context between the current partial processing region and at least one previous partial processing region by inputting the extracted feature into the RNN, and
• generate an image processing result for the input image frame based on the updated hidden state.

An electronic device, comprising:

• a camera configured to generate an input image frame;
• a memory configured to store instructions;
• and
• a processor configured to execute the instructions stored in the memory to:
• extract a feature of a current partial processing region of an input image frame by inputting pixel data of the current partial processing region into a convolutional neural network (CNN),
• update a hidden state of a recurrent neural network (RNN) for a context between the current partial processing region and at least one previous partial processing region by inputting the extracted feature into the RNN, and
• generate an image processing result for the input image frame based on the updated hidden state.

An apparatus comprising:

• a processor;
• and
• a memory configured to store instructions executable by the processor,
• wherein in response to the instructions being executed by the processor, the processor is configured to:
• extract a feature of a current partial processing region of an input image frame using a convolutional neural network (CNN),
• determine whether the current partial processing region of the input image frame is a final partial processing region of the input image frame,
• in a case in which the current partial processing region is not the final partial processing region, repeatedly update a hidden state of a recurrent neural network (RNN) by inputting the extracted feature of the current partial processing region into the RNN, generate intermediate context data based on the updated hidden state, and generate an intermediate detection result based on the intermediate context data until the current partial processing region is the final partial processing region, and
• in a case in which the current partial processing region is the final partial processing region, update the hidden state of the RNN by inputting the extracted feature of the current partial processing region into the RNN, generate final context data based on the updated hidden state, and generate an image processing result for the input image frame based on the final context data.

An apparatus comprising:

• a processor;
• and
• a memory configured to store instructions executable by the processor,
• wherein in response to the instructions being executed by the processor, the processor is configured to:
• extract a feature of a current partial processing region of an input data frame using a convolutional neural network (CNN),
• update a hidden state of a recurrent neural network (RNN) by inputting the extracted feature into the RNN,
• generate context data based on the updated hidden state,
• generate a detection result based on the context data,
• determine whether the detection result indicates the presence of target data in the input data frame,
• in a case in which the detection result indicates the presence of the target data in the input data frame, terminate any further processing of the input data frame, and
• in a case in which the detection result does not indicate the presence of the target data in the input data frame, continue processing of the input data frame with respect to a partial processing region of the input data frame that is subsequent to the current partial processing region.