99 results about "Motion computation" patented technology

A system, method, and computer program product for providing a user with a virtual environment in which the user can perform guided activities and receive feedback are described. The user is provided with guidance to perform certain movements. The user's movements are captured in an image stream. The image stream is analyzed to estimate the user's movements, which is tracked by a user-specific human model. Biomechanical quantities such as center of pressure and muscle forces are calculated based on the tracked movements. Feedback such as the biomechanical quantities and differences between the guided movements and the captured actual movements are provided to the user.

An image processing apparatus for performing a tracking of a moving object by setting a tracking area corresponding to a moving object appearing in a video image, by setting a plurality of feature points in the tracking area, and by tracking the plurality of feature points, comprises a tracking processing unit for tracking each of the plurality of feature points from the preceding frame to the present frame, and a motion calculation processing unit for specifying a position of the tracking area in the present frame by estimating the motion of the tracking area based the tracking result of each of the feature points, wherein the tracking processing unit calculates reliability indicating the height of the possibility that a feature point exists in the moving object to each of the feature points, and the motion calculation processing unit calculates the motion of the tracking area by using the reliability.

A stereoscopic computer graphics (CG) moving image generating apparatus includes a projection transformation section for generating a two-dimensional projection image as viewed from a camera using three-dimensional structural information of a subject; rendering sections for calculating a viewable image from the output of the projection transformation section; a camera sequence generating section for generating camera parameters defining projection transformation in the projection transformation section and capable of generating a moving image by varying the same; a motion calculating section for calculating the motion and/or motion parallax of a displayed subject using at least one of the three-dimensional structural information, the output of the projection transformation section, the output of the rendering sections, and the output of the camera sequence generating section; and a camera parameter correcting section for automatically or manually correcting the camera parameter so that the motion and/or motion parallax of the displayed subject do not exceed a tolerance range of a viewer, based at least on the output of the motion calculating section, the size of a screen for image display, and the viewing distance of the viewer.

A scaleable video encoder has one or more encoding modes in which at least some, and possibly all, of the motion information used during motion-based predictive encoding of a video stream is excluded from the resulting encoded video bitstream, where a corresponding video decoder is capable of performing its own motion computation to generate its own version of the motion information used to perform motion-based predictive decoding in order to decode the bitstream to generate a decoded video stream. All motion computation, whether at the encoder or the decoder, is preferably performed on decoded data. For example, frames may be encoded as either H, L, or B frames, where H frames are intra-coded at full resolution and L frames are intra-coded at low resolution. The motion information is generated by applying motion computation to decoded L and H frames and used to generate synthesized L frames. L-frame residual errors are generated by performing inter-frame differencing between the synthesized and original L frames and are encoded into the bitstream. In addition, synthesized B frames are generated by tweening between the decoded H and L frames and B-frame residual errors are generated by performing inter-frame differencing between the synthesized B frames and, depending on the implementation, either the original B frames or sub-sampled B frames. These B-frame residual errors are also encoded into the bitstream. The ability of the decoder to perform motion computation enables motion-based predictive encoding to be used to generate an encoded bitstream without having to expend bits for explicitly encoding any motion information.

A system, method, and computer program product for generating dynamically feasible whole-body motion of a humanoid robot while realizing specified upper-body task motion are described. A kinematically feasible upper-body motion is generated based on the specified upper-body motion. A series of zero-moment points (ZMP) are computed for the generated motion and used to determine whether such motion is dynamically feasible. If the motion is not dynamically feasible, then the torso acceleration is modified to make the motion dynamically feasible, and otherwise synchronized as needed. A series of modified ZMP is determined based on the modified torso acceleration and used to distribute the resultant net ground reaction force and moment to the two feet.

In a mobile body motion calculation apparatus (100), a corresponding point calculation section (101) calculates corresponding points between images captured by a camera 120. A first motion calculation section (102) calculates a first motion (Ma) of a mobile body using the corresponding points, assuming a predetermined plane in the images. A second motion calculation section (103) calculates a second motion (Mb) using the first motion (Ma) and the corresponding points.

A method for static and moving object detection employing a motion computation method based on spatio-temporal tensor formulation, a foreground and background modeling method, and a multi-cue appearance comparison method. The invention operates in the presence of shadows, illumination changes, dynamic background, and both stopped and removed objects.

In a digital camera or other image acquisition device, motion vectors between successive image frames of an object scene are calculated from normalized values of pixel luminance in order to reduce or eliminate any effects on the motion calculation that might occur when the object scene is illuminated from a time varying source such as a fluorescent lamp. Calculated motion vectors are checked for accuracy by a robustness matrix.

A real-time computer vision system tracks one or more objects moving in a scene using a target location technique which does not involve searching. The imaging hardware includes a color camera, frame grabber and processor. The software consists of the low-level image grabbing software and a tracking algorithm. The system tracks objects based on the color, motion and/or shape of the object in the image. A color matching function is used to compute three measures of the target's probable location based on the target color, shape and motion. The method then computes the most probable location of the target using a weighting technique. Once the system is running, a graphical user interface displays the live image from the color camera on the computer screen. The operator can then use the mouse to select a target for tracking. The system will then keep track of the moving target in the scene in real-time.

A motion calculation device includes an image-capturing unit configured to capture an image of a range including a plane and outputs the captured image, an extraction unit configured to extract a region of the plane from the image, a detection unit configured to detect feature points and motion vectors of the feature points from a plurality of images captured by the image-capturing unit at a predetermined time interval; and a calculation unit configured to calculate the motion of the host device based on both of an epipolar constraint relating to the feature points and a homography relating to the region.

Provided are an image processing system, an image processing method, and a program for adjusting an image quality of a fluorescent light motion image. An image obtaining section that obtains a high image-quality motion image and a low image-quality motion image in which a same subject is captured simultaneously; a motion calculating section that calculates a motion of the subject in the high image-quality motion image, from the high image-quality motion image; and an image adjusting section that generates a motion image resulting from adjusting an image quality of the low image-quality motion image, based on the motion calculated by the motion calculating section are included, to adjust an image quality of a low image-quality motion image. Accordingly, the image quality of a low image-quality image can be improved.

In the image capturing apparatus, the controller controls an optical element, when a motion of the image capturing apparatus follows a motion of the object, by using first motion information obtained from a first detector to detect the motion of the image capturing apparatus and second motion information obtained from a second detector to detect the motion of the object. The calculator calculates prediction information on the motion of the object during an exposure time, by using the second information detected at multiple times before the exposure time. The controller uses the prediction information to control the optical element during the exposure time.

Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.

The invention mainly belongs to the technical field of target invasion detection and particularly relates to an unmanned aerial vehicle image-based region invasion target detection method. The method is used for target detection of an unmanned aerial vehicle. The method comprises the steps of performing Gaussian pyramid layering on an original image in an original video obtained by a vehicle-mounted camera of the unmanned aerial vehicle to lower calculation complexity of feature point extraction; and then extracting SIFT feature points of the image to perform image registration, capturing motion information in the image by adopting LK sparse optical flow of a pyramid to realize target point motion calculation, performing motion point clustering and false target removal, and finally performing target judgment to realize target detection. According to the method, the search range of inter-frame feature points of the unmanned aerial vehicle video can be reduced, the motion large-displacement problem in the unmanned aerial vehicle image is solved, and the detection capability is improved; and therefore, the manual detection intensity of region invasion is reduced and the automatic perception capability of the unmanned aerial vehicle is improved.

A low power image sensor sensing light from an object and outputting an image signal includes: an image sensing unit which senses light from an object, converts the light into an electric signal, and outputs the electric signal; a comparing unit which receives an electric signal from the image sensor, compares a voltage level of the electric signal with a reference voltage, and outputs an image signal as an 1bit signal per pixel; and an effective image adjuster which compares bit value distribution of an image signal output from the comparator with a preset effective range, and adjusts the effective image to output an effective image. Further, an optical pointing device includes: an image sensor which senses light from an object and outputs an image signal; and a motion computing unit which receives the image signal and compares before and after images to calculate a motion vector, wherein the motion computing unit includes: a temporary storage unit to temporarily store image data output from the image sensor; a comparator to compare the image data output from the image sensor with the image data stored in the temporary storage unit; a direction selector; and a controller.

Provided is an apparatus and method for transmitting packets in a wireless network. The apparatus includes a motion calculation unit, a transmission repetition adjustment unit, and a packet transmission repetition unit, The, motion calculation unit calculates the motion value of a mobile terminal. The transmission repetition adjustment unit receives N-value determination information and determines the number of repetitions (N value) of transmission of a packet transmitted and received by the mobile terminal based on the received N-value determination information, and the motion value calculated by the motion calculation unit. The packet transmission repetition unit repeatedly transmits the packet, which is received from a data link layer, to a physical layer according to the N value determined by the transmission repetition adjustment unit.

An image processing apparatus comprising: a block selector that selects one of blocks that contain an amount of features, larger than a predetermined amount of features, from among a plurality of blocks which compose a particular one of a plurality of frames of a moving image of a subject; a motion calculator that calculates a motion vector of each of blocks of a second particular one of the plurality of frames next to the first-mentioned particular frame and corresponding to a respective one of the selected blocks; a displacement calculator that calculates a displacement of the second particular frame based on the calculated motion vectors; and an image shake corrector that corrects an image shake in the moving image based on the calculated displacement.

A data acquisition method and device for motion recognition, a motion recognition system and a computer readable storage medium are disclosed. The data acquisition device for motion recognition comprises: an initial motion recognition module adapted to perform an initial recognition with respect to motion data collected by a sensor and provide motion data describing a predefined range around a motion trigger point to a data storage module for storage; a data storage module adapted to store motion data provided from the initial motion recognition module; and a communications module adapted to forward the motion data stored in the data storage module to a motion computing device for motion recognition. The present invention makes an initial selection to the motion data to be transmitted to the motion computing device under the same sampling rate. Consequently, the present invention reduces pressures on wireless channel transmission and wireless power consumption, and provides high accuracy in motion recognition while providing motion data at the same sampling rate.