Abstract: A method for motion synchronization-based head pose estimation, by a head mounted display (HMD) device and an HMD device for performing the same are provided. The method includes receiving, by the HMD device, motion data from a plurality of motion sensors of the HMD device, receiving, by the HMD device, a plurality of image frames from at least one simultaneous localization and mapping SLAM camera of the HMD device, estimating, by the HMD device, a plurality of motion parameters of head movements of a user from the plurality of image frames received from memory, generating, by the HMD device, a filtered subset of the motion data received from the plurality of motion sensors based on the plurality of motion parameters of the head movements, synchronizing, by the HMD device, the plurality of image frames received from the memory and filtered subset of motion data, and estimating, by the HMD device, the head pose based on the synchronized plurality of image frames and motion data.

Abstract: Embodiments of the disclosure provide a method for accelerating an asset execution in an electronic device. The method includes: detecting, by the electronic device, a user interface (UI) transition associated with a first application; predicting, by the electronic device, a sequence of at least one asset to be offloaded for a subsequent UI transition based on an asset parameter using a ML model, wherein the subsequent UI transition is associated with the first application or a second application; offloading, by the electronic device, the at least one asset in the sequence; and storing, by the electronic device, the at least one offloaded asset to a memory of the electronic device.

Abstract: Provided are a method and apparatus for controlling an unresponsive state of an electronic device. The method includes: obtaining a plurality of device parameters related to at least one of a hardware module and a software module of the electronic device, and a user usage pattern parameter based on receiving at least one user input to the electronic device; predicting the unresponsive state of the electronic device based on the collected plurality of device parameters and the collected user usage pattern parameter; and avoiding the predicted unresponsive state of the electronic device by applying a policy selected from among a plurality of policies associated with the plurality of the device parameters to a device parameter related to the predicted unresponsive state of the electronic device.

Abstract: Embodiments of the disclosure provide a method for accelerating an asset execution in an electronic device. The method includes: detecting, by the electronic device, a user interface (UI) transition associated with a first application; predicting, by the electronic device, a sequence of at least one asset to be offloaded for a subsequent UI transition based on an asset parameter using a ML model, wherein the subsequent UI transition is associated with the first application or a second application; offloading, by the electronic device, the at least one asset in the sequence; and storing, by the electronic device, the at least one offloaded asset to a memory of the electronic device.

Abstract: Provided are a method and apparatus for controlling an unresponsive state of an electronic device. The method includes: obtaining a plurality of device parameters related to at least one of a hardware module and a software module of the electronic device, and a user usage pattern parameter based on receiving at least one user input to the electronic device; predicting the unresponsive state of the electronic device based on the collected plurality of device parameters and the collected user usage pattern parameter; and avoiding the predicted unresponsive state of the electronic device by applying a policy selected from among a plurality of policies associated with the plurality of the device parameters to a device parameter related to the predicted unresponsive state of the electronic device.