Abstract: An apparatus directed to improvements of position-dependent intra prediction sample filtering process in video coding is provided. The apparatus receives a compressed bitstream and performs an intra prediction process based on an intra prediction mode for a current block to generate an intra predicted sample for a current sample in the current block. The apparatus determines a weight array based on the intra prediction mode for the current block, from a plurality of weight arrays, each of the plurality of weight arrays being associated with a respective one of a plurality of intra prediction modes, determines a weight from the determined weight array based on a position of the current sample, and generate a modified intra predicted sample for the current sample based on the determined weight and the intra predicted sample for the current sample.

Abstract: A method includes obtaining a gesture sample via a gesture classifier. The gesture sample includes parameters of features extracted from the radar signals based on user motion in performance of a gesture. The method includes determining whether to obtain feedback for a target gesture associated with the gesture sample. The method includes in response to a determination to obtain the feedback, obtaining the feedback for the target gesture. The feedback includes a label indicating a type of gesture. The method includes determining whether the gesture sample associated with the label is valid based on comparison to a dataset of pre-existing validated gesture samples and a distance threshold. The method includes in response to determining that the gesture sample associated with the label is valid, determining whether to update a model for the gesture classifier using the validated gesture sample as a training sample.

Abstract: An apparatus for three dimensional (3D) art viewing includes one or more sensors and a processor operably coupled to the one or more sensors. The processor is configured to detect, using the one or more sensors, a position of a user. The processor is additionally configured to output, for display, an aspect of an image based on the position of the user. The processor is also configured to obtain, using the one or more sensors, movement data associated with a movement of the user. The processor is further configured to apply temporal smoothing to smooth the movement data. In addition, the processor is configured to map the smoothed movement data to a series of view indices. The processor is also configured to change the aspect of the image for display based on the mapped series of view indices.

Abstract: Methods and systems for user velocity tracking using wireless technology. A computer-implemented method includes receiving an input, receiving a video feed including a plurality of frames, selecting a subset of the plurality of frames based on the input, generating at least one alternate frame based on at least one original frame of the selected subset, replacing the at least one original frame in the selected subset with the at least one alternate frame to generate an altered video feed, and displaying the altered video feed on a display. An alternative replay generation system is configured receive a video feed including a plurality of frames, select a subset of the plurality of frames, generate at least one alternate frame based, and replace at least one original frame in the selected subset with the at least one alternate frame to generate an altered video feed.

Abstract: An apparatus includes a communication interface configured to receive a bitstream for a compressed video and a processor operably coupled to the communication interface. The processor is configured to decode the bitstream for the compressed video and obtain reference samples associated with a block of a video frame. The processor is also configured to select a down-sampling filter to use in down-sampling the reference samples. The processor is also configured to apply the selected down-sampling filter to the reference samples to obtain reduced reference samples. The processor is also configured to obtain a reduced intra prediction associated with the block using the reduced reference samples. The processor is also configured to select an up-sampling filter to use in up-sampling the reduced intra prediction. The processor is also configured to apply the selected up-sampling filter to the reduced intra prediction to obtain a full intra prediction of the block.

Abstract: An apparatus includes a communication interface configured to receive a bitstream for a compressed video and a processor operably coupled to the communication interface. The processor is configured to decode the bitstream for the compressed video and obtain reference samples associated with a block of a video frame. The processor is also configured to determine an interpolation filter type for use in obtaining predicted samples. The processor is also configured to select an interpolation filter of the interpolation filter type based on a block size of the block of the video frame. The processor is also configured to apply the interpolation filter to the reference samples. The processor is also configured to output one or more predicted samples using the interpolated reference samples.

Abstract: A method includes obtaining a gesture sample via a gesture classifier. The gesture sample includes parameters of features extracted from the radar signals based on user motion in performance of a gesture. The method includes determining whether to obtain feedback for a target gesture associated with the gesture sample. The method includes in response to a determination to obtain the feedback, obtaining the feedback for the target gesture. The feedback includes a label indicating a type of gesture. The method includes determining whether the gesture sample associated with the label is valid based on comparison to a dataset of pre-existing validated gesture samples and a distance threshold. The method includes in response to determining that the gesture sample associated with the label is valid, determining whether to update a model for the gesture classifier using the validated gesture sample as a training sample.

Abstract: An electronic device includes a transceiver configured to transmit and receive radar signals. The electronic device further comprises a processor operatively coupled to the transceiver. The processor is configured to adjust a field of view (FoV) associated with the transceiver based on a plurality of radar frames corresponding to the radar signals, extract a plurality of feature vectors from the plurality of radar frames based on the adjusted FoV. The processor is further configured to identify an activity based on the plurality of feature vectors, perform a gesture magnitude operation, and perform an action based on the gesture and a result of the gesture magnitude operation.

Abstract: An electronic device includes a transceiver configured to transmit and receive radar signals and a processor operatively coupled to the transceiver. The processor is configured to identify, based on the received radar signals, a plurality of radar frames related to an activity of a target. The processor is further configured to extract a plurality of features from the plurality of radar frames, compute burst attributes for the extracted features, predict a gesture based on the burst attributes, determine whether the predicted gesture is a valid gesture, and if the predicted gesture is a valid gesture, perform an action corresponding to the predicted gesture.

Abstract: An electronic device includes a transceiver configured to transmit and receive radar signals, and a processor operatively coupled to the transceiver. The processor is configured to extract a plurality of feature vectors from a plurality of radar frames corresponding to the radar signals, identify an activity based on the plurality of feature vectors, and determine whether the identified activity corresponds with a non-gesture. The processor is further configured to, if the activity fails to correspond with a non-gesture, identify a gesture that corresponds with the activity, and perform an action corresponding with the identified gesture.

Abstract: An electronic device for object rigging includes a processor. The processor is configured to obtain a three-dimensional (3D) scan of an object. The processor is also configured to identify 3D coordinates associated with joints of the 3D scan. The processor is further configured to identify parameters associated with fitting a 3D parametric body model to the 3D scan based on the 3D coordinates of the joints. Additionally, the processor is configured to modify the parameters to reduce 3D joint errors between the 3D coordinates associated with the joints on the 3D scan and the 3D parametric body model. The processor is also configured to generate a rigged 3D scan based on the modified parameters, for performing an animated motion.

Abstract: A method for warning a wearer of a pacemaker against potential electromagnetic interference by a radar-aided mobile device is provided. The method includes obtaining sensor data from a sensor of an electronic device. The method includes detecting electromagnetic interference (EMI) risk based on the sensor data obtained. The method includes determining whether a condition for executing an EMI risk mitigation function is satisfied, based on the detected EMI risk. The method includes, in response to determining that the condition for executing the EMI risk mitigation function is satisfied, performing the EMI risk mitigation function. In some embodiments, performing the EMI risk mitigation function includes at least one of: adjusting a radio frequency (RF) transmit power; and outputting an alert that warns a user of the electronic device about a pacemaker in relation to the detected EMI risk.

Abstract: A method includes obtaining a stream of radar data into a sliding input data window composed of recent radar frames from the stream. Each radar frame within the data window includes features selected from a predefined feature set and at least one of time-velocity data or time angle data. The method includes, for each radar frame within the data window, receiving a binary prediction indicating whether the radar frame includes a gesture end. The method includes in response to the binary prediction indicating that the radar frame includes the gesture end, triggering an early stop (ES) checker to determine whether an ES condition is satisfied. Determining whether the ES condition is satisfied comprises determining whether a noise frames condition and a valid activity condition are satisfied. The method includes in response to a determination that the ES condition is satisfied, triggering a gesture classifier to predict a gesture type.

Abstract: A method includes obtaining a target distance and target velocity for each radar frame within a sliding input data window. Each radar frame within the data window includes extracted features. The method includes determining a dynamic threshold distance (dth) for a range of distances wherein performance of a gesture is valid. The method includes determining whether the target distance corresponding to a current radar frame satisfies a proximity condition based on the dth. The method includes in response to a determination the proximity condition is not satisfied, detecting a start of activity based on the extracted features. The method includes segmenting gesture frames from non-gesture frames in the data window, in response to at least one of: a determination the first proximity condition is satisfied, or a determination the current radar frame includes an end of the activity. The method includes discarding the non-gesture frames to modify the data window.

Abstract: An apparatus for three dimensional (3D) art viewing includes one or more sensors and a processor operably coupled to the one or more sensors. The processor is configured to detect, using the one or more sensors, a position of a user. The processor is additionally configured to output, for display, an aspect of an image based on the position of the user. The processor is also configured to obtain, using the one or more sensors, movement data associated with a movement of the user. The processor is further configured to apply temporal smoothing to smooth the movement data. In addition, the processor is configured to map the smoothed movement data to a series of view indices. The processor is also configured to change the aspect of the image for display based on the mapped series of view indices.

Abstract: An electronic device for object rigging includes a processor. The processor is configured to obtain a 3D scan of an object. The processor is also configured to match a rigged parametric model to the 3D scan by minimizing a surface distance and 3D joint errors between the rigged parametric model and the 3D scan. The processor is further configured to identify a correspondence between the rigged parametric model and the 3D scan. Additionally, the processor is configured to transfer attributes of the rigged parametric model to the 3D scan based on the correspondence to generate a rigged 3D scan. The processor is also configured to apply animation motion to the rigged 3D scan. The rigged 3D scan with the applied animation motion is rendered on a display.

Abstract: An electronic device for object rigging includes a processor. The processor is configured to obtain a three-dimensional (3D) scan of an object. The processor is also configured to identify 3D coordinates associated with joints of the 3D scan. The processor is further configured to identify parameters associated with fitting a 3D parametric body model to the 3D scan based on the 3D coordinates of the joints. Additionally, the processor is configured to modify the parameters to reduce 3D joint errors between the 3D coordinates associated with the joints on the 3D scan and the 3D parametric body model. The processor is also configured to generate a rigged 3D scan based on the modified parameters, for performing an animated motion.

Abstract: An electronic device for object rigging includes a processor. The processor is configured to obtain a 3D scan of an object. The processor is also configured to match a rigged parametric model to the 3D scan by minimizing a surface distance and 3D joint errors between the rigged parametric model and the 3D scan. The processor is further configured to identify a correspondence between the rigged parametric model and the 3D scan. Additionally, the processor is configured to transfer attributes of the rigged parametric model to the 3D scan based on the correspondence to generate a rigged 3D scan. The processor is also configured to apply animation motion to the rigged 3D scan. The rigged 3D scan with the applied animation motion is rendered on a display.