Abstract: Information processing that effectively uses emotion data indicating a user emotion for each scene of a moving image content is disclosed. In one example, an extraction unit extracts an emotion representative scene on the basis of emotion metadata having user emotion information for each scene of the moving image content. Reproduction of a part of the moving image content and editing of extracting a part of the moving image content can be effectively performed on the basis of the extracted emotion representative scene. For example, the extraction unit extracts the emotion representative scene on the basis of a type of the user emotion or a degree of the user emotion.

Abstract: Effective use of a user emotion for each scene of moving image content is enabled. On the basis of a user emotion and video quality for each scene of moving image content A, correlation data obtained by associating the user emotion with the video quality is generated. The user emotion for each scene of moving image content B is predicted on the basis of the video quality for each scene of the moving image content B and the correlation data obtained by associating the user emotion with the video quality related to the moving image content A. For example, the predicted user emotion for each scene of the moving image content B is displayed and used.

Abstract: An imaging device according to the present disclosure includes an exposure section and a controller. The controller controls, at an exposure timing based on a predicted exposure timing at which a state of a subject shot at a first frame rate is predicted to satisfy a predetermined condition, the exposure section at a second frame rate. The second frame rate is different from the first frame rate.

Abstract: An imaging device according to the present disclosure includes an exposure section and a controller. The controller controls, at an exposure timing based on a predicted exposure timing at which a state of a subject shot at a first frame rate is predicted to satisfy a predetermined condition, the exposure section at a second frame rate. The second frame rate is different from the first frame rate.

Abstract: A camera of the present disclosure includes an imaging section, a zooming section, a framing section, and a controller. The controller controls, in a case where one of the zooming section and the framing section is operated by a user operation, another of the zooming section and the framing section that is not operated by the user operation, in accordance with a movement of a subject.

Abstract: Various aspects of a method and a system for image processing are disclosed herein. The method includes processing an input image, which comprises structure information and detail information, using image processing (IP) blocks in an image processing pipeline. One or more of the IP blocks, such as the “lossy” IP blocks, process the input image with at least a partial loss of the detail information. By replacing the “lossy” IP blocks with redesigned image processing (IP) modules, the image processing pipeline reduces or avoids such loss of the detail information. A more efficient implementation of the improved pipeline is realized by using a master IP module when the “lossy” IP blocks are reordered and grouped together in the image processing pipeline. The method is further extended to process 3-D images to reduce or avoid loss of detail information in a 3-D image processing pipeline.

Abstract: There is provided an image processing device including a color determination unit configured to detect a region in a certain color from an input image, a feature amount calculating unit configured to calculate a feature amount related to luminance of the input image, and a noise reduction unit configured to perform noise removal on the input image on the basis of a result obtained by detecting the region in the certain color, and the feature amount.

Abstract: Various aspects of a method and a system for image processing are disclosed herein. The method includes processing an input image, which comprises structure information and detail information, using image processing (IP) blocks in an image processing pipeline. One or more of the IP blocks, such as the “lossy” IP blocks, process the input image with at least a partial loss of the detail information. By replacing the “lossy” IP blocks with redesigned image processing (IP) modules, the image processing pipeline reduces or avoids such loss of the detail information. A more efficient implementation of the improved pipeline is realized by using a master IP module when the “lossy” IP blocks are reordered and grouped together in the image processing pipeline. The method is further extended to process 3-D images to reduce or avoid loss of detail information in a 3-D image processing pipeline.

Abstract: According to an embodiment of the present disclosure, there is provided an image processing apparatus including a detection unit, a strength determination unit, and a processor. The detection unit is configured to detect at least one area in an image. The strength determination unit is configured to determine strength of processing for a unit of processing of the image, based on a distance between a location of the area being detected by the detection unit and a location of the unit of processing of the image. The processor is configured to perform the processing on the image, per the unit of processing, at the strength being determined by the strength determination unit.

Abstract: There is provided an image processing device including a color determination unit configured to detect a region in a certain color from an input image, a feature amount calculating unit configured to calculate a feature amount related to luminance of the input image, and a noise reduction unit configured to perform noise removal on the input image on the basis of a result obtained by detecting the region in the certain color, and the feature amount.

Abstract: According to an embodiment of the present disclosure, there is provided an image processing apparatus including a detection unit, a strength determination unit, and a processor. The detection unit is configured to detect at least one area in an image. The strength determination unit is configured to determine strength of processing for a unit of processing of the image, based on a distance between a location of the area being detected by the detection unit and a location of the unit of processing of the image. The processor is configured to perform the processing on the image, per the unit of processing, at the strength being determined by the strength determination unit.