Abstract: A child care apparatus includes a horizontal reciprocating motion mechanism, a vertical reciprocating motion mechanism, and a supporting device. The horizontal reciprocating motion mechanism includes a mounting cover. The vertical reciprocating motion mechanism is disposed at the mounting cover. The vertical reciprocating motion mechanism includes a lifting component and a driving mechanism for driving the lifting component to move, the lifting component is located in the mounting cover and passes through the mounting cover to extend out of the mounting cover, and the mounting cover is configured to limit rotation of the lifting component. The supporting device is located outside the mounting cover and is disposed on the lifting component. The child care apparatus has advantages of low noise, good balance, and good stability.

Abstract: A baby bassinet includes a supporting bracket, a cradle, a sliding mechanism, and a driving mechanism. Two supporting rods are vertically arranged on an upper portion of the supporting bracket. At least one guide shaft is connected between the supporting rods. The sliding mechanism includes a connecting base, at least one housing fixed to the connecting base, and at least three rolling pieces. Two through holes are defined on two ends of the at least one housing. The at least one guide shaft passes through the through holes. The at least three rolling pieces are uniformly arranged in the at least one housing around the at least one guide shaft. The at least three rolling pieces abut against the at least one guide shaft to roll on the at least one guide shaft when the at least one housing moves relative to the at least one guide shaft.

Abstract: Embodiments are described for dynamically adapting video encoding to maintain a nearly stable frame rate based on processor capabilities and bandwidth, for example, by varying a quantization parameter. The quality of the encoded video can be varied to maintain the nearly constant frame rate, which may be measured from the number of encoded video frames being transmitted over a network interface.

Abstract: A video encoder may be put in a starve mode during a low latency operation in which the video encoder may be operated in a mode that allows video frames to be encoded without any interdependencies such as motion compensation. At least one encoding parameter of the video encoding is selected such that, for each resulting encoded video frame, the video frame fits in exactly one application layer packet.

Abstract: A video encoder may be put in a starve mode during a low latency operation in which the video encoder may be operated in a mode that allows video frames to be encoded without any interdependencies such as motion compensation. At least one encoding parameter of the video encoding is selected such that, for each resulting encoded video frame, the video frame fits in exactly one application layer packet.

Abstract: A video encoder may be put in a starve mode during a low latency operation in which the video encoder may be operated in a mode that allows video frames to be encoded without any interdependencies such as motion compensation. At least one encoding parameter of the video encoding is selected such that, for each resulting encoded video frame, the video frame fits in exactly one application layer packet.

Abstract: Embodiments are described for dynamically adapting video encoding to maintain a nearly stable frame rate based on processor capabilities and bandwidth, for example, by varying a quantization parameter. The quality of the encoded video can be varied to maintain the nearly constant frame rate, which may be measured from the number of encoded video frames being transmitted over a network interface.

Abstract: In one embodiment, a method includes receiving multimedia content information associated with at least one segment of a multimedia content, receiving a request to view the at least one segment of the multimedia content from a client device, logging playback information associated with the viewing of the at least one segment of the multimedia content, determining a multimedia quality metric associated with the at least one segment of multimedia content based in part upon a portion of the received multimedia content information and a portion of the logged playback information, and classifying the at least one segment of the multimedia content with the multimedia quality metric.

Abstract: Embodiments are described for dynamically adapting video encoding to maintain a nearly stable frame rate based on processor capabilities and bandwidth, for example, by varying a quantization parameter. The quality of the encoded video can be varied to maintain the nearly constant frame rate, which may be measured from the number of encoded video frames being transmitted over a network interface.

Abstract: In one embodiment, a method includes receiving multimedia content information associated with at least one segment of a multimedia content, receiving a request to view the at least one segment of the multimedia content from a client device, logging playback information associated with the viewing of the at least one segment of the multimedia content, determining a multimedia quality metric associated with the at least one segment of multimedia content based in part upon a portion of the received multimedia content information and a portion of the logged playback information, and classifying the at least one segment of the multimedia content with the multimedia quality metric.

Abstract: A video encoder may be put in a starve mode during a low latency operation in which the video encoder may be operated in a mode that allows video frames to be encoded without any interdependencies such as motion compensation. At least one encoding parameter of the video encoding is selected such that, for each resulting encoded video frame, the video frame fits in exactly one application layer packet.

Abstract: Embodiments are described for dynamically adapting video encoding to maintain a nearly stable frame rate based on processor capabilities and bandwidth, for example, by varying a quantization parameter. The quality of the encoded video can be varied to maintain the nearly constant frame rate, which may be measured from the number of encoded video frames being transmitted over a network interface.

Abstract: Decoding tasks are identified for decoding encoded video. Decoding tasks may include entropy decoding tasks, motion compensation tasks, inverse frequency transform tasks, inverse quantization tasks, intra decoding tasks, loop filtering tasks, or other tasks. Task dependencies are identified for the video decoding tasks. For example, one or more decoding tasks may depend on prior completion of entropy decoding tasks. The decoding tasks are prioritized based at least in part on the task dependencies. For example, a higher priority may be assigned to tasks that must be completed before other tasks that depend on them can begin. Prioritized decoding tasks are selected to be performed by hardware threads. For example, a first hardware thread may perform a first decoding task that does not depend on any uncompleted tasks while a second hardware thread performs a second decoding task that does not depend on any uncompleted tasks.

Abstract: Decoding tasks are identified for decoding encoded video. Decoding tasks may include entropy decoding tasks, motion compensation tasks, inverse frequency transform tasks, inverse quantization tasks, intra decoding tasks, loop filtering tasks, or other tasks. Task dependencies are identified for the video decoding tasks. For example, one or more decoding tasks may depend on prior completion of entropy decoding tasks. The decoding tasks are prioritized based at least in part on the task dependencies. For example, a higher priority may be assigned to tasks that must be completed before other tasks that depend on them can begin. Prioritized decoding tasks are selected to be performed by hardware threads. For example, a first hardware thread may perform a first decoding task that does not depend on any uncompleted tasks while a second hardware thread performs a second decoding task that does not depend on any uncompleted tasks.

Abstract: Decoding tasks are identified for decoding encoded video. Decoding tasks may include entropy decoding tasks, motion compensation tasks, inverse frequency transform tasks, inverse quantization tasks, intra decoding tasks, loop filtering tasks, or other tasks. Task dependencies are identified for the video decoding tasks. For example, one or more decoding tasks may depend on prior completion of entropy decoding tasks. The decoding tasks are prioritized based at least in part on the task dependencies. For example, a higher priority may be assigned to tasks that must be completed before other tasks that depend on them can begin. Prioritized decoding tasks are selected to be performed by hardware threads. For example, a first hardware thread may perform a first decoding task that does not depend on any uncompleted tasks while a second hardware thread performs a second decoding task that does not depend on any uncompleted tasks.

Abstract: A multiple bitrate (MBR) video encoding management tool utilizes available processing units for parallel MBR video encoding. Instead of focusing only on multi-threading of encoding tasks for a single picture or group of pictures (GOP), the management tool parallelizes the encoding of multiple GOPs between different processing units and/or different computing systems. With this parallel MBR video encoding architecture, different GOPs can be encoded in parallel. To facilitate such parallel encoding, data dependencies between GOPs are removed. The management tool can adjust the number of GOPs to encode in parallel on a computing system so as to favor parallelism of encoding for different GOPs at the expense of parallelism of encoding inside a GOP, or vice versa, and thereby set a suitable balance between encoding latency and throughput.

Abstract: Various examples are disclosed herein that relate to staged element classification. For example, one disclosed example provides a method of classifying elements by forming elements for classification into a plurality of first-level sets in a first stage, generating primary groups within the first-level sets based on element similarity, forming a plurality of second-level sets from the first-level sets in a second stage, generating secondary groups within the second-level sets based on element similarity, and merging a plurality of the primary and/or secondary groups based on element similarity.

Abstract: The subject disclosure relates to face recognition in video. Face detection data in frames of input data are used to generate face galleries, which are labeled and used in recognizing faces throughout the video. Metadata that associates the video frame and the face are generated and maintained for subsequent identification. Faces other than those found by face detection may be found by face tracking, in which facial landmarks found by the face detection are used to track a face over previous and/or subsequent video frames. Once generated, the maintained metadata may be accessed to efficiently determine the identity of a person corresponding to a viewer-selected face.

Abstract: Decoding tasks are identified for decoding encoded video. Decoding tasks may include entropy decoding tasks, motion compensation tasks, inverse frequency transform tasks, inverse quantization tasks, intra decoding tasks, loop filtering tasks, or other tasks. Task dependencies are identified for the video decoding tasks. For example, one or more decoding tasks may depend on prior completion of entropy decoding tasks. The decoding tasks are prioritized based at least in part on the task dependencies. For example, a higher priority may be assigned to tasks that must be completed before other tasks that depend on them can begin. Prioritized decoding tasks are selected to be performed by hardware threads. For example, a first hardware thread may perform a first decoding task that does not depend on any uncompleted tasks while a second hardware thread performs a second decoding task that does not depend on any uncompleted tasks.