Abstract: A head mounted display and a control method thereof are disclosed. The control method comprises following steps. An application processor controls a pico projector unit to project a virtual image having a virtual object located on a virtual image coordinate in a virtual image coordinate system. An eye image sensing unit captures an eye image data. A sensing apparatus senses a touch object to output a sensing data. An ASIC obtains a real image coordinate of the touch object in a real image coordinate system according to the sensing data. The ASIC obtains a pupil position according to the eye image data, and controls the adjustment unit to adjust an imaging position of the virtual image according to the pupil position. The ASIC determines whether the touch object touched the virtual object according to the pupil position, the real coordinate and the virtual coordinate.

Abstract: A head mounted display (HMD) and an imaging method thereof are provided. The HMD comprises a beam splitter, a pico projector, an application processor, an eye image sensor, an adjustment apparatus, an application specific integrated circuit (ASIC), and an eyeglass frame. The application processor controls the pico projector to project a beam. The eye image sensor captures an eye image. The ASIC performs a perspective correction on the eye image to generate a frontal eye image. The ASIC obtains a beam location of the beam and obtains a pupil location according to the frontal eye image. The ASIC according to the beam location and the pupil location controls the adjustment apparatus to adjust the beam splitter. The eyeglass frame carries the beam splitter, the pico projector, the application processor, the eye image sensor and the ASIC.

Abstract: An example process to enhance a two-dimensional (2D) image may include generating a depth map for the 2D image based on edges detected from the 2D image, wherein the depth map can be used to convert the 2D image to a 3D image. The process may further include enhancing the 2D image using the depth map.

Abstract: A head mounted system includes a physiological signal sensor, a signal processing circuit, a memory, an application processor, and an eyeglass frame. The physiological signal sensor monitors a physiological state to output a physiological signal. The signal processing circuit determines whether the physiological state is abnormal according to the physiological signal. When it is not abnormal, the signal processing circuit controls the physiological signal sensor to monitor the physiological state at a first monitoring frequency. When it is abnormal, the signal processing circuit outputs a warning signal, and controls the physiological signal sensor to monitor the physiological state at a second monitoring frequency greater than the first monitoring frequency. The application processor receives the warning signal and stores physiological data corresponding to the physiological signal in the memory.

Abstract: A head mounted system is provided. The head mounted system includes an auxiliary image capturing device, a main image capturing device, a signal processing circuit, a memory, an application processor, and an eyeglass frame. The auxiliary image capturing device detects an abnormal situation. The signal processing circuit outputs a warning signal and makes the main image capturing device start video recording when the abnormal situation occurs. The application processor receives the warning signal and stores video data, after the video recording starting, in the memory. The eyeglass frame carries the auxiliary image capturing device, the main image capturing device, the signal processing circuit, the memory, and the application processor.

Abstract: A method for controlling an exposure duration of a high dynamic range image, including: consecutively generating a first high dynamic range image having a first exposure duration ratio and a second high dynamic range image having a second exposure duration ratio greater than the first exposure duration ratio; performing image quality evaluations on both the first high dynamic range image and the second high dynamic range image to obtain a first image quality and a second image quality, respectively; and determining whether the second image quality is better than the first image quality; if yes, generating a third high dynamic range image having a third exposure duration ratio greater than the second exposure duration ratio; if not, generating the third high dynamic range image having the first exposure duration ratio and setting the first exposure duration ration as the optimal exposure duration ratio.

Abstract: An eye-accommodation-aware head mounted visual assistant system and an imaging method thereof are disclosed. The eye-accommodation-aware head mounted visual assistant system comprises a beam splitter, a projecting light source, an image sensor, a calculating device, a controlling device, and an eyeglass frame. The projecting light source projects assistant information via beam splitter. The image sensor captures an eye image. The calculating device calculates an object distance and a viewing direction according to the eye image. The controlling device according to the object distance controls the projecting light source to adjust an image location of the assistant information, and controls the projecting light source to adjust a projecting light angle and an angle of the beam splitter according to the viewing direction. The eyeglass frame carries the projecting light source, the beam splitter, the image sensor, the calculating device and the controlling device.

Abstract: A time domain signal analysis method is provided. The signal analysis method includes the following steps. A signal to be analyzed is received. The signal to be analyzed is iteratively sifted by using Empirical Mode Decomposition (EMD) to extract at least one intrinsic function (IMF). A normalized Hilbert transform is performed on the IMF. The transformed IMF includes phase information. The transformed IMF is processed by means of phase processing to obtain the processed IMF including angular frequency information. The foregoing signal analysis method could be utilized in an ultrasound imaging system to identify image information of ultrasound images.

Abstract: Realization of sleep and reconnecting functions is developed for network systems which comprise a number of end devices, network path sharing devices and coordinators. End devices and, even, network path sharing devices can be enforced to enter a sleep state at the first preset times and wake up at the second preset times. The two preset times are either assigned offline or adjustable at run time, according to the actual traffic load in the network. When a node wakes up, it checks whether the corresponding parent node is in the active state or not. If the corresponding parent node is not in the active state, the node will find a new parent node to establish a new transmission path.

Abstract: In accordance with at least some embodiments of the present disclosure, a processor for performing stereo matching of a first image and a second image is described. The processor may include a first pipeline stage configured to generate data costs associated with a first tile selected from the first image, wherein the data costs is generated based on pixels in the first tile and corresponding pixels in the second image. The processor may include a second pipeline stage configured to generate disparity values associated with the first tile and an outbound message from the first tile to one of neighboring tiles in the first image, wherein the disparity values and the outbound message are generated based on the data costs and inbound messages from the neighboring tiles to the first tile.

Abstract: An image processing method is provided. The image processing method includes the following steps. A plurality of raw signal is received by a signal transceiving module of the ultrasound imaging system. It is determined whether each of the raw signals satisfies any condition in a condition group, and the raw signal satisfying any condition in the condition group is mapped to one of a plurality of preset constants to generate a plurality of first data. The raw signals not satisfying any condition in the condition group are processed according to a calculation formula to generate a plurality of second data. A beamforming procedure is simultaneously performed on the first and second data to obtain a beamformed image. The beamformed image is transformed to obtain an image of a region to be detected. Furthermore, an imaging system using the foregoing image processing method is also provided.

Abstract: In a system and method of viewer centric depth adjustment, a sensor measures viewing distance of a viewer from a screen; and a depth remapping unit receives a color image, a depth map and the viewing distance, and accordingly remaps depth values of the depth map such that the viewer perceives same depth at different viewing distances.

Abstract: A system and method of correcting a depth map for 3D image is disclosed. A spatial spectral transform unit extracts pixels of object boundaries according to an input image, wherein the spatial spectral transform unit adopts Hilbert-Huang transform (HHT). A correction unit corrects an input depth map corresponding to the input image according to the pixels of object boundaries, thereby resulting in an output depth map.

Abstract: A method of revising depth of a three-dimensional (3D) image is disclosed. The method comprises the following steps: firstly, at least one initial depth map associated with one image of the 3D image pair based on stereo matching technique is received, wherein the one image comprises a plurality of pixels, and the initial depth map carries an initial depth value of each pixel. Then, the inconsistence among the pixels of the one image of the 3D image pair is detected to estimate a reliable map. Finally, the initial depth value is interpolated according to the reliable map and the proximate pixels, so as to generate a revised depth map by revising the initial depth value.

Abstract: In accordance with at least some embodiments of the present disclosure, a process for generating a depth map for converting a two-dimensional (2D) image to a three-dimensional (3D) image is described. The process may include generating a depth gradient map from the 2D image, wherein the depth gradient map is configured to associate one or more edge counts with one or more depth values, extracting an image component from the 2D image, wherein the image component is associated with a color component in a color space, determining a set of gains to adjust the depth gradient map based on the image component, and generating the depth map by performing depth fusion based on the depth gradient map and the set of gains.

Abstract: A method for determining a number of bits for encoding an audio signal comprising a core audio signal portion and a residual audio signal portion is described that comprises selecting, from the residual audio signal portion, a reference residual audio signal portion and at least one candidate residual audio signal portion; comparing the reference residual audio signal portion with the candidate residual audio signal portion; and determining the number of bits for encoding the audio signal depending on the result of the comparison.

Abstract: An image processing method is provided. The image processing method includes the following steps. A plurality of raw signal is received by a signal transceiving module of the ultrasound imaging system. It is determined whether each of the raw signals satisfies any condition in a condition group, and the raw signal satisfying any condition in the condition group is mapped to one of a plurality of preset constants to generate a plurality of first data. The raw signals not satisfying any condition in the condition group are processed according to a calculation formula to generate a plurality of second data. A beamforming procedure is simultaneously performed on the first and second data to obtain a beamformed image. The beamformed image is transformed to obtain an image of a region to be detected. Furthermore, an imaging system using the foregoing image processing method is also provided.

Abstract: A time domain signal analysis method is provided. The signal analysis method includes the following steps. A signal to be analyzed is received. The signal to be analyzed is iteratively sifted by using Empirical Mode Decomposition (EMD) to extract at least one intrinsic function (IMF). A normalized Hilbert transform is performed on the IMF. The transformed IMF includes phase information. The transformed IMF is processed by means of phase processing to obtain the processed IMF including angular frequency information. The foregoing signal analysis method could be utilized in an ultrasound imaging system to identify image information of ultrasound images.

Abstract: Embodiments of the invention provides a method and device for assigning bitrates to a plurality of channels in a scalable audio encoding/truncation process. Different bitrates are assigned to different channels in the scalable audio encoding/truncation process.

Abstract: In accordance with at least some embodiments of the present disclosure, a process for converting a two-dimensional (2D) image based on edge information is described. The process may include partitioning the 2D image to generate a plurality of blocks, segmenting the plurality of blocks into a group of regions based on edges determined in the plurality of blocks, assigning depth values to the plurality of blocks based on a depth gradient hypothesis associated with the group of regions, wherein pixels in each of the plurality of blocks are associated with a same depth value, and generating the depth map based on the depth values of the plurality of blocks.