Patent classifications
G11B27/13
Voice-based video tagging
Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. A video summary can be generated including one or more of the identified best scenes. The video summary can be generated using a video summary template with slots corresponding to video clips selected from among sets of candidate video clips. Best scenes can also be identified by receiving an indication of an event of interest within video from a user during the capture of the video. Metadata patterns representing activities identified within video clips can be identified within other videos, which can subsequently be associated with the identified activities.
ENCODING INFORMATION ON TAPE USING WRITE OFFSET GAPS
As disclosed herein a method for encoding information on tape using write offset gaps. The method includes receiving a request to write a dataset on a tape medium using a plurality of head groups, and identifying information to be encoded when writing the dataset. The method further includes determining a head group offset pattern that encodes the information, and writing the dataset using the head group offset pattern. Also disclosed herein is a method for decoding information on tape using write offset gaps. The method includes reading a dataset from a tape medium using a plurality of head groups, and determining a head group offset pattern used to read the dataset. The method further includes decoding information encoded in the head group offset pattern to provide decoded information. A computer program product corresponding to the above method is also disclosed herein.
Scene and activity identification in video summary generation based on motion detected in a video
Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. In one example, best scenes are identified based on the motion values associated with frames or portions of a frame of a video. Motion values are determined for each frame and portions of the video including frames with the most motion are identified as best scenes. Best scenes may also be identified based on the motion profile of a video. The motion profile of a video is a measure of global or local motion within frames throughout the video. For example, best scenes are identified from portion of the video including steady global motion. A video summary can be generated including one or more of the identified best scenes.
Scene and activity identification in video summary generation based on motion detected in a video
Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. In one example, best scenes are identified based on the motion values associated with frames or portions of a frame of a video. Motion values are determined for each frame and portions of the video including frames with the most motion are identified as best scenes. Best scenes may also be identified based on the motion profile of a video. The motion profile of a video is a measure of global or local motion within frames throughout the video. For example, best scenes are identified from portion of the video including steady global motion. A video summary can be generated including one or more of the identified best scenes.
Scene and activity identification in video summary generation based on motion detected in a video
Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. In one example, best scenes are identified based on the motion values associated with frames or portions of a frame of a video. Motion values are determined for each frame and portions of the video including frames with the most motion are identified as best scenes. Best scenes may also be identified based on the motion profile of a video. The motion profile of a video is a measure of global or local motion within frames throughout the video. For example, best scenes are identified from portion of the video including steady global motion. A video summary can be generated including one or more of the identified best scenes.
Scene and activity identification in video summary generation based on motion detected in a video
Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. In one example, best scenes are identified based on the motion values associated with frames or portions of a frame of a video. Motion values are determined for each frame and portions of the video including frames with the most motion are identified as best scenes. Best scenes may also be identified based on the motion profile of a video. The motion profile of a video is a measure of global or local motion within frames throughout the video. For example, best scenes are identified from portion of the video including steady global motion. A video summary can be generated including one or more of the identified best scenes.
Encoding information on tape using write offset gaps
As disclosed herein a method for encoding information on tape using write offset gaps. The method includes receiving a request to write a dataset on a tape medium using a plurality of head groups, and identifying information to be encoded when writing the dataset. The method further includes determining a head group offset pattern that encodes the information, and writing the dataset using the head group offset pattern. Also disclosed herein is a method for decoding information on tape using write offset gaps. The method includes reading a dataset from a tape medium using a plurality of head groups, and determining a head group offset pattern used to read the dataset. The method further includes decoding information encoded in the head group offset pattern to provide decoded information. A computer program product corresponding to the above method is also disclosed herein.
Scene and activity identification in video summary generation
Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. A video summary can be generated including one or more of the identified best scenes. The video summary can be generated using a video summary template with slots corresponding to video clips selected from among sets of candidate video clips. Best scenes can also be identified by receiving an indication of an event of interest within video from a user during the capture of the video. Metadata patterns representing activities identified within video clips can be identified within other videos, which can subsequently be associated with the identified activities.
Scene and activity identification in video summary generation
Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. A video summary can be generated including one or more of the identified best scenes. The video summary can be generated using a video summary template with slots corresponding to video clips selected from among sets of candidate video clips. Best scenes can also be identified by receiving an indication of an event of interest within video from a user during the capture of the video. Metadata patterns representing activities identified within video clips can be identified within other videos, which can subsequently be associated with the identified activities.
INFORMATION PROCESSING APPARATUS AND METHOD, AND PROGRAM
An information processing apparatus including a plurality of feature amount extraction parts which extract, from content, a plurality of feature amounts that contain information concerning a camera motion in a frame of the content. A display control part displays frames of the content and a GUI on the displayed content frame. The GUI corresponds to an operation concerning the camera motion on the basis of the extracted camera motion information.