Abstract:
Embodiments of the present disclosure are directed to a method for storing and processing data. The method includes identifying a database in a memory of a host device having one or more rows and one or more columns. A partition having a partition size is identified, and the one or more rows of the database is identified based on the partition size. The data stored in the one or more rows is converted into a column-based format, and the data is stored in a computational storage device in the column-based format. The computational storage device is configured to retrieve the data stored in the column-based format, in response to a query, and process the query based on the data.
Abstract:
A processor implemented method of processing a facial expression image, the method includes controlling a camera to capture a first facial expression image and a second facial expression image, acquiring a first expression feature of the first facial expression image, acquiring a second expression feature of the second facial expression image, generating a new expression feature dependent on differences between the acquired first expression feature and the acquired second expression feature, and adjusting a target facial expression image based on the new expression feature.
Abstract:
A gaze estimation method includes receiving, by a processor, input data including a current image and a previous image each including a face of a user, determining, by the processor, a gaze mode indicating a relative movement between the user and a camera that captured the current image and the previous image based on the input data, and estimating, by the processor, a gaze of the user based on the determined gaze mode, wherein the determined gaze mode is one of a plurality of gaze modes comprising a stationary mode and a motion mode.
Abstract:
An apparatus and corresponding method are provided to match images and include assigning depth candidate values to a pixel in a first image, and reassigning third depth candidate values to a first pixel in the first image based on first depth candidate values assigned to the first pixel and second depth candidate values assigned to a second pixel adjacent to the first pixel. The apparatus and method also include determining one of the third depth candidate values to be a depth value of the first pixel, and matching the first pixel and a third pixel in a second image corresponding to the determined depth value of the first pixel.
Abstract:
A method and apparatus for detecting a three-dimensional (3D) point cloud point of interest (POI), the apparatus comprising a 3D point cloud data acquirer to acquire 3D point cloud data, a shape descriptor to generate a shape description vector describing a shape of a surface in which a pixel point of a 3D point cloud and a neighboring point of the pixel point are located, and a POI extractor to extract a POI based on the shape description vector is disclosed.
Abstract:
A processor-implemented method with video processing includes: determining a first image feature of a first image of video data and a second image feature of a second image that is previous to the first image; determining a time-domain information fusion processing result by performing time-domain information fusion processing on the first image feature and the second image feature; and determining a panoptic segmentation result of the first image based on the time-domain information fusion processing result.
Abstract:
A method of shuffling data may include shuffling a first batch of data using a first memory on a first level of a memory hierarchy to generate a first batch of shuffled data, shuffling a second batch of data using the first memory to generate a second batch of shuffled data, and storing the first batch of shuffled data and the second batch of shuffled data in a second memory on a second level of the memory hierarchy. The method may further include merging the first batch of shuffled data and the second batch of shuffled data. A data shuffling device may include a buffer memory configured to stream one or more records to a partitioning circuit and transfer, by random access, one or more records to a grouping circuit.
Abstract:
A gaze estimation method and apparatus is disclosed. The gaze estimation method includes obtaining an image including an eye region of a user, extracting, from the obtained image, a first feature of data, obtaining a second feature of data used for calibration of a neural network model, and estimating a gaze of the user using the first feature and the second feature.
Abstract:
A gaze tracking method and apparatus, and a gaze tracking neural network training method and apparatus are provided. The gaze tracking apparatus includes one or more processors and a memory, and the one or more processors obtain output position information from an input face image of a user using a neural network model, determines a position adjustment parameter for the user, and predicts gaze position information of the user by adjusting the output position information based on the position adjustment parameter.
Abstract:
A storage system includes: a storage device to store an array of data elements associated with a sort operation; a storage interface to facilitate communications between the storage device and a host computer; and a reconfigurable processing device communicably connected to the storage device, the reconfigurable processing device including: memory to store input data read from the storage device, the input data corresponding to the array of data elements stored in the storage device; and a kernel including one or more compute components to execute the sort operation on the input data stored in the memory according to a SORT command received from the host computer. The reconfigurable processing device is to dynamically instantiate the one or more compute components to accelerate the sort operation.