Abstract: A semiconductor protection device includes: an N-type epitaxial layer, a device isolation layer disposed in the N-type epitaxial layer, an N-type drift region disposed below the device isolation layer, an N-type well disposed in the N-type drift region, first and second P-type drift regions, respectively disposed to be in contact with the device isolation layer, and spaced apart from the N-type drift region, first and second P-type doped regions, respectively disposed in the first and second P-type drift regions, first and second N-type floating wells, respectively disposed in the first and second P-type drift regions to be spaced apart from the first and second P-type doped regions, and disposed to be in contact with the device isolation layer, and first and second contact layer, respectively disposed to cover the first and second N-type floating well, to be in contact with the device isolation layer.

Abstract: Provided is a method of framing a three dimensional (3D) target object for generation of a virtual camera layout. The method may include analyzing a reference video image to extract a framing rule for at least one reference object in the reference video image, generating a framing rule for at least one 3D target object using the framing rule for the at least one reference object in the reference video image, and using the framing rule for the at least one 3D target object for generation of a virtual camera layout.

Abstract: Provided is a method of framing a three dimensional (3D) target object for generation of a virtual camera layout. The method may include analyzing a reference video image to extract a framing rule for at least one reference object in the reference video image, generating a framing rule for at least one 3D target object using the framing rule for the at least one reference object in the reference video image, and using the framing rule for the at least one 3D target object for generation of a virtual camera layout.

Abstract: Disclosed are a method and apparatus for processing an image based on an artificial neural network. The method separates an input image into a foreground image including a subject and a background image including remaining objects except for the subject, estimates camera framing for the subject based on the input image and the foreground image, configures a feature vector based on an optical flow map extracted from the input image, estimates camera work using the feature vector, and outputs at least one selected from between the camera framing and the camera work.