A video creation method includes a first recording step of reading out the pixel signals from the plurality of pixels, creating a video of a first angle of view at a first thinning-out rate, and recording first video data, and a second recording step of, in a case where a target subject exists in the first angle of view, creating a video of a second angle of view including the target subject and having a second angle of view smaller than the first angle of view at a second thinning-out rate lower than the first thinning-out rate, and recording second video data.

A video creation method includes a first recording step of reading out the pixel signals from the plurality of pixels, creating a video of a first angle of view at a first thinning-out rate, and recording first video data, and a second recording step of, in a case where a target subject exists in the first angle of view, creating a video of a second angle of view including the target subject and having a second angle of view smaller than the first angle of view at a second thinning-out rate lower than the first thinning-out rate, and recording second video data.

The present disclosure provides an image encoder. The image encoder is configured to encode an original image and reduce compression loss. The image encoder comprises an image signal processor and a compressor. The image signal processor is configured to receive a first frame image and a second frame image and generates a compressed image of the second frame image using a boundary pixel image of the first frame image. The image signal processor may include memory configured to store first reference pixel data which is the first frame image. The compressor is configured to receive the first reference pixel data from the memory and generate a bitstream obtained by encoding the second frame image based on a difference value between the first reference pixel data and the second frame image. The image signal processor generates a compressed image of the second frame image using the bitstream generated by the compressor.

The present disclosure provides an image encoder. The image encoder is configured to encode an original image and reduce compression loss. The image encoder comprises an image signal processor and a compressor. The image signal processor is configured to receive a first frame image and a second frame image and generates a compressed image of the second frame image using a boundary pixel image of the first frame image. The image signal processor may include memory configured to store first reference pixel data which is the first frame image. The compressor is configured to receive the first reference pixel data from the memory and generate a bitstream obtained by encoding the second frame image based on a difference value between the first reference pixel data and the second frame image. The image signal processor generates a compressed image of the second frame image using the bitstream generated by the compressor.

Techniques for video analytics of captured video content are described. An apparatus may comprise a flash memory, a serial bus, and a processor circuit coupled to the flash memory and the serial bus. The processor circuit may comprise a multi-core central processing unit (CPU) and an integrated graphics processing unit (GPU). The processor circuit may receive captured video content via a local communication link, perform video analytics on the captured video content; and send data associated with the performed video analytics to a network interface, for communication to a remote device via a network communication link. Other examples are described and claimed.

Techniques for video analytics of captured video content are described. An apparatus may comprise a flash memory, a serial bus, and a processor circuit coupled to the flash memory and the serial bus. The processor circuit may comprise a multi-core central processing unit (CPU) and an integrated graphics processing unit (GPU). The processor circuit may receive captured video content via a local communication link, perform video analytics on the captured video content; and send data associated with the performed video analytics to a network interface, for communication to a remote device via a network communication link. Other examples are described and claimed.

Access point pictures designated as randomly accessible positions are I pictures or P pictures. Information indicating the decoding sequence (I1, P1, B1, B2, B3, B4, P2, . . . ) of pictures functioning as access points and attribute information (picture_type) indicating whether a picture functions as an access point or is necessary for decoding of the access point following a given access point are recorded on the video information recording medium. Random access is possible even if the GOP interval is lengthened.

A method and transmitting system for processing data are discussed. The method according to an embodiment includes randomizing enhanced data; first encoding the randomized enhanced data to add first parity data for error correction, thereby forming a frame; dividing data of the frame into a plurality of groups, wherein the plurality of groups have a same size; first interleaving data of each group; second interleaving the first-interleaved data; encoding signaling information at a code rate; and transmitting a broadcast signal including the second-interleaved enhanced data and the encoded signaling information. Second encoding on the randomized enhanced data is selectively performed, wherein, when the second encoding is performed, second parity data for error detection are added to the randomized enhanced data. The signaling information includes transmission parameters to indicate whether the second encoding is performed.

In one embodiment, a computing device receives, from one or more cameras, a video stream comprising multiple frames, where the video stream is received at a first quality. The computing device analyzes, using a machine-learning model, images in the frames, where the machine-learning model has been trained to detect one or more objects-of-interest in the images. The computing device identifies a sequence-of-interest including consecutive frames of the video stream, where at least one object-of-interest was detected in at least one of the consecutive frames. The computing device generates a video package including the sequence-of-interest.

In one embodiment, a computing device receives, from one or more cameras, a video stream comprising multiple frames, where the video stream is received at a first quality. The computing device analyzes, using a machine-learning model, images in the frames, where the machine-learning model has been trained to detect one or more objects-of-interest in the images. The computing device identifies a sequence-of-interest including consecutive frames of the video stream, where at least one object-of-interest was detected in at least one of the consecutive frames. The computing device generates a video package including the sequence-of-interest.