10563results about How to "Reduce computational complexity" patented technology

An improved system and method for providing improved inter-layer prediction for extended spatial scalability in video coding, as well as improving inter-layer prediction for motion vectors in the case of extended spatial scalability. In various embodiments, for the prediction of macroblock mode, the actual reference frame index and motion vectors from the base layer are used in determining if two blocks should be merged. Additionally, multiple representative pixels in a 4×4 block can be used to represent each 4×4 block in a virtual base layer macroblock. The partition and motion vector information for the relevant block in the virtual base layer macroblock can be derived from all of the partition information and motion vectors of those 4×4 blocks.

The invention discloses a density evolution based polarization code constructing method and polarization code coding and decoding system. According to the invention, the code length N and the information bit length K of an information code to be processed are obtained, an expectation value set of a log-likelihood ratio probability density function of N bit channels, K bit channels are selected as the information bit channels according to the expectation value set and information bit information index vector quantity is generated; an information bit sequence and a fixed bit sequence are mixed and the mixed bit vector quantity is multiplied by a polarization code for generating a matrix so as to output an encoding sequence; the encoding sequence is modulated and input into a transmission channel and the sequence output by the transmission channel is subjected to decoding operation by adopting a polarization code decoding algorithm, bit error probability and frame error rate of the decoded code are calculated and a design signal to noise ratio is changed, the above operation is repeated until the bit error probability and frame error rate become the minimum. The method and system provided by the invention are suitable for general binary system memoryless channels, the bit error probability and frame error rate are low, the calculation complexity is low and the communication performance of a communication system is improved.

A post processing de-blocking filter includes a threshold determination unit for adaptively determining a plurality of threshold values according to at least differences in quantization parameters QPs of a plurality of adjacent blocks in a received video stream and to a user defined offset (UDO) allowing the threshold levels to be adjusted according to the UDO value; an interpolation unit for performing an interpolation operation to estimate pixel values in an interlaced field if the video stream comprises interlaced video; and a de-blocking filtering unit for determining a filtering range specifying a maximum number of pixels to filter around a block boundary between the adjacent blocks, determining a region mode according to local activity around the block boundary, selecting one of a plurality of at least three filters, and filtering a plurality of pixels around the block boundary according to the filtering range, the region mode, and the selected filter.

A novel and useful apparatus for and method of Gaussian Minimum Shift Keying (GMSK) single antenna interference cancellation (SAIC) for use in a digital receiver. The invention comprises an interference mitigation module that treats the problem of GMSK SAIC in a blind manner. The interference mitigation mechanism is operative to compensate for the co-channel interference added in the communications channel which is subject to multipath propagation and fading, receiver filter and any pre-channel estimation filtering. The interference mitigation module takes advantage of the spatial diversity making up multiple branches of the received signal. The branches comprise the in-phase and quadrature elements of the received signal, the sampling phases if over sampling is applied (i.e. T / m sampling) and / or multiple antennas. The invention utilizes the spatial diversity of these multiple representations of the received signal and combines (i.e. collapses) the information in the plurality of branches into a single branch that is input to the equalizer.

A high security identification card includes an on-board memory for stored biometric data and an on-board sensor for capturing live biometric data. An on-board processor on the card performs a matching operation to verify that the captured biometric data matches the locally stored biometric data. Only if there is a positive match is any data transmitted from the card for additional verification and / or further processing. Preferably, the card is ISO SmartCard compatible. In one embodiment, the ISO SmartCard functions as a firewall for protecting the security processor used for storing and processing the protected biometric data from malicious external attack via the ISO SmartCard interface. In another embodiment, the security processor is inserted between the ISO SmartCard Interface and an unmodified ISO SmartCard processor and blocks any external communications until the user's fingerprint has been matched with a previously registered fingerprint. Real-time feedback is provided while the user is manipulating his finger over the fingerprint sensor, thereby facilitating an optimal placement of the finger over the sensor. The card may be used to enable communication with a transactional network or to obtain physical access into a secure area.

A post processing de-blocking filter includes a threshold determination unit for adaptively determining a plurality of threshold values according to at least differences in quantization parameters QPs of a plurality of adjacent blocks in a received video stream and to a user defined offset (UDO) allowing the threshold levels to be adjusted according to the UDO value; an interpolation unit for performing an interpolation operation to estimate pixel values in an interlaced field if the video stream comprises interlaced video; and a de-blocking filtering unit for determining a filtering range specifying a maximum number of pixels to filter around a block boundary between the adjacent blocks, determining a region mode according to local activity around the block boundary, selecting one of a plurality of at least three filters, and filtering a plurality of pixels around the block boundary according to the filtering range, the region mode, and the selected filter.

The present invention discloses method for moving target detection and tracking in a complex scene. The method comprises two steps of multiple moving target detection and multiple moving target tracking: in the multiple moving target detection, a background model based on self adapting nonparametric kernel density estimation is established with the aim at the monitoring of the complex scene, therefore the disturbance of the movement of tiny objects can be effectively suppressed, the target shadow is eliminated, and the multiple moving target is detected; in the multiple moving target tracking, the target model is established, the moving state of the target is confirmed through ''matching matrix'', and corresponding tracking strategy is adopted according to the different movement condition of the target. Target information is ''recovered'' through the probabilistic reasoning method, and the target screening degree of the target is analyzed with the aim at the problem that multiple targets screen mutually. The algorithm of the present invention can well realize the moving target tracking, obtains the trace of the moving target, and has good real time and ability of adapting to the environmental variation. The present invention has wide application range and high accuracy, therefore being a core method for intelligent vision monitoring with versatility.

The invention aims to provide a method for drawing viewpoints by reinforcing an interested region, comprising the following steps of: aiming at the collection mode of a light field camera, firstly establishing the camera geometrical model of the collection mode of the light field camera according to the parameters of a collection system and the geometrical information of a scene, then calculatingthe interested region and reinforcing the original thin depth map through the identified interested region; and then carrying out light field drawing by utilizing the reinforced depth map according to camera parameters and a geometrical scene to obtain a new viewpoint image. The test on the method indicates that the invention can obtain favorable viewpoint reestablishing quality.

The invention belongs to crossing field of computer vision and intelligent robots and discloses a variational mechanism-based large-area indoor scene reconstruction method. The method comprises the following steps: step 1, acquiring calibration parameters of a camera, and building an aberration correcting model; step 2, building a camera position and gesture depiction and camera projection model; step 3, utilizing an SFM-based monocular SFM (Space Frequency Modulation) algorithm to realize camera position and gesture estimation; step 4, building a variational mechanism-based depth map estimation model, and performing solving on the model; and step 5, building a key frame selection mechanism to realize three-dimensional scene renewal. According to the invention, an RGB (Red Green Blue) camera is adopted to acquire environmental data, and a variational mechanism-based depth map generation method is proposed through utilizing a high-precision monocular positioning algorithm, so that quick large-area indoor three-dimensional scene reconstruction is realized, and problems of three-dimensional reconstruction algorithm cost and real-time performance are effectively solved.

A post processing de-blocking filter includes a threshold determination unit for adaptively determining a plurality of threshold values according to at least differences in quantization parameters QPs of a plurality of adjacent blocks in a received video stream and to a user defined offset (UDO) allowing the threshold levels to be adjusted according to the UDO value; an interpolation unit for performing an interpolation operation to estimate pixel values in an interlaced field if the video stream comprises interlaced video; and a de-blocking filtering unit for determining a filtering range specifying a maximum number of pixels to filter around a block boundary between the adjacent blocks, determining a region mode according to local activity around the block boundary, selecting one of a plurality of at least three filters, and filtering a plurality of pixels around the block boundary according to the filtering range, the region mode, and the selected filter.

A post processing de-blocking filter includes a threshold determination unit for adaptively determining a plurality of threshold values according to at least differences in quantization parameters QPs of a plurality of adjacent blocks in a received video stream and to a user defined offset (UDO) allowing the threshold levels to be adjusted according to the UDO value; an interpolation unit for performing an interpolation operation to estimate pixel values in an interlaced field if the video stream comprises interlaced video; and a de-blocking filtering unit for determining a filtering range specifying a maximum number of pixels to filter around a block boundary between the adjacent blocks, determining a region mode according to local activity around the block boundary, selecting one of a plurality of at least three filters, and filtering a plurality of pixels around the block boundary according to the filtering range, the region mode, and the selected filter.

A post processing de-blocking filter includes a threshold determination unit for adaptively determining a plurality of threshold values according to at least differences in quantization parameters QPs of a plurality of adjacent blocks in a received video stream and to a user defined offset (UDO) allowing the threshold levels to be adjusted according to the UDO value; an interpolation unit for performing an interpolation operation to estimate pixel values in an interlaced field if the video stream comprises interlaced video; and a de-blocking filtering unit for determining a filtering range specifying a maximum number of pixels to filter around a block boundary between the adjacent blocks, determining a region mode according to local activity around the block boundary, selecting one of a plurality of at least three filters, and filtering a plurality of pixels around the block boundary according to the filtering range, the region mode, and the selected filter.

The invention relates to a combined dispatching method for uplink multi-point cooperation in LTE-A. The method comprises following steps: 1) determining cooperative and non-operative dispatching user; 2) dispatching of cooperative user in cell; 3) combined resource dispatching for cooperative user of cell; 4) dispatching for non-cooperative user of cell. The invention adopts stepping optimizing method in cell or intercell, and simultaneously considers user dispatching priority and channel relation in combined dispatching in cell, reduces interference between users of shared frequency cooperation, promotes throughout of whole system while guaranteeing user fairness and possesses low computation complexity.

An apparatus and method for encoding and decoding a voice signal. The apparatus includes an encoder configured to generate an output bitstream signal from an input voice signal. The output bitstream signal is associated with at least a first standard of a first plurality of CELP voice compression standards. Additionally, the apparatus includes a decoder configured to generate an output voice signal from an input bitstream signal. The input bitstream signal is associated with at least a first standard of a second plurality of CELP voice compression standards. The CELP encoder includes a plurality of codec-specific encoder modules. Additionally, the CELP encoder includes a plurality of generic encoder modules. The CELP decoder includes a plurality of codec-specific decoder modules. Additionally, the CELP decoder includes a plurality of generic decoder modules.

Methods for motion estimation with adaptive motion accuracy of the present invention include several techniques for computing motion vectors of high pixel accuracy with a minor increase in computation. One technique uses fast-search strategies in sub-pixel space that smartly searches for the best motion vectors. An alternate technique estimates high-accurate motion vectors using different interpolation filters at different stages in order to reduce computational complexity. Yet another technique uses rate-distortion criteria that adapts according to the different motion accuracies to determine both the best motion vectors and the best motion accuracies. Still another technique uses a VLC table that is interpreted differently at different coding units, according to the associated motion vector accuracy.

A joint search method for UAV multiobjective path planning in an urban low altitude environment first constructs a static safety index map based on static known obstacles. Meanwhile, based on proactively detected obstacles that are not marked on a geographic map by a UAV, the method constructs online a dynamic safety index map. Second, a multiobjective path planning problem is solved using a joint offline and online search method. Moreover, this method first plans offline the least cost path from a starting point to an end point and then invokes the online search scheme to replan online a changed path when the UAV detects unknown obstacles. Thus, the UAV can avoid dynamic obstacles effectively. The online search scheme has a small search space and can quickly replan a safe path for the UAV, thus satisfying the requirement of UAV on the real-time path planning.

The embodiment of the invention discloses an image prediction method and a relevant device. The image prediction method comprises the following steps: determining the motion vector predictors of K pixel samples in a current image block, wherein K is an integer greater than 1, the K pixel samples comprise a first vertex angle pixel sample of the current image block, the motion vector predictor of the first vertex angle pixel sample is obtained on the basis of the motion vector of a preset first spatial domain adjacent image block of the current image block, and the first spatial domain adjacent image block is adjacent to a first vertex angle pixel sample spatial domain; and predicting the pixel value of the current image block on the basis of a non-translational motion model and the motion vector predictors of the K pixel samples. According to the scheme in the embodiment of the invention, the computation complexity of image prediction based on the non-translational motion model is lowered.

The invention discloses a face recognition method and system, in particular relates to a face recognition model training method and system. The face recognition method comprises the following steps: every user for recognition is trained and a face recognition model is obtained; within the set face posture range, the face image with structure light coding and the face image without structure light coding of the present user waiting for recognition are collected simultaneously; a face range image is obtained based on the face image with structure light coding, and a face gray image is obtained based on the face image without structure light coding; the face gray image is used for calibration, and face pre-treatment is conducted for the face gray image and the face range image based on the calibration results; the characteristics of pretreated face range image and face gray image are calculated respectively; the characteristics are input to the face recognition model to recognize faces and output face recognition results. The technical proposal provided by the invention can reduce the interference of light to face recognition and reduce costs simultaneously.

A data-driven lithium ion battery cycle life prediction method based on an AR (Autoregressive) model and an RPF (Regularized Particle Filtering) algorithm relates to a lithium ion battery cycle life prediction method and belongs to the technical field of data prediction. The invention solves the problems in the existing lithium ion battery cycle life prediction method that the model-based prediction method is complicated in modeling, and parameters are difficult to identify. The data-driven lithium ion battery cycle life prediction method combines time sequence analysis with particle filter method and comprises the following steps: the AR model is firstly utilized to realize the multi-step prediction on battery performance degradation process time sequence data; and then, aiming at the problem of uncertainty expression of the cycle life prediction result, the regularized particle filtering method is introduced, and a lithium ion battery cycle life prediction method framework is proposed. The method proposed by the invention can be used for effectively predicating the cycle life of a lithium ion battery and realizes the output of probability density distribution of the predication result, has good computational efficiency and uncertainty expression ability.

The invention discloses a gesture recognition method based on 3D-CNN and convolution LSTM. The method comprises the steps that the length of a video input into 3D-CNN is normalized through a time jitter policy; the normalized video is used as input to be fed to 3D-CNN to study the short-term temporal-spatial features of a gesture; based on the short-term temporal-spatial features extracted by 3D-CNN, the long-term temporal-spatial features of the gesture are studied through a two-layer convolutional LSTM network to eliminate the influence of complex backgrounds on gesture recognition; the dimension of the extracted long-term temporal-spatial features are reduced through a spatial pyramid pooling layer (SPP layer), and at the same time the extracted multi-scale features are fed into the full-connection layer of the network; and finally, after a latter multi-modal fusion method, forecast results without the network are averaged and fused to acquire a final forecast score. According to the invention, by learning the temporal-spatial features of the gesture simultaneously, the short-term temporal-spatial features and the long-term temporal-spatial features are combined through different networks; the network is trained through a batch normalization method; and the efficiency and accuracy of gesture recognition are improved.

The invention provides a source coding method based on polar codes. The method includes the steps that firstly, a symbol value set of source restoring signals is determined, through an optimal symbol-to-bit mapping rule, a source symbol sequence is mapped into a bit soft information sequence in a serial mode, polar code serial offset coding is conducted on the bit soft information sequence, a coding path with the maximal reliability value is found, a bit sequence corresponding to the coding path is output, and finally the most important part of bits are selected from the bit sequence through a reliable bit set to serve as a coding result. The search width of the coding path is increased through a serial offset coding method, and the selection probability of the correct coding path is increased. The reliable bit set can assist a coder in distinguishing the most important bits in the coding process, the most important bits are output, and then the coding length can be compressed. In addition, the method can flexibly configure coding parameters and the symbol-to-bit mapping rule, the calculation complexity is low, and the coding performance is excellent.

A novel and useful apparatus for and method of multiple input multiple output (MIMO) detection for use in MIMO based communication systems. The mechanism of the invention performs a simplified tree search utilizing a single stage expansion of the most likely first symbol candidates, in the case of a 2×2 MIMO system. The invention also provides a refinement mechanism that is operative to significantly improve the soft information (i.e. log likelihood ratio) of the list of candidates. To improve the soft information, the mechanism applies one or more refinements rounds to generate additional candidates for both first and second detected symbols.

The invention discloses an image forecasting method and a related device. The image forecasting method includes: confirming K1 pixel samples in an image block x, and confirming a candidate movement information unit set corresponding to each of the K1 pixel samples; enabling each candidate movement information unit set corresponding to each pixel sample to include at least one candidate movement information unit; confirming a merger movement information unit set i which includes K1 movement information units; using a non-translation movement model and the merger movement information unit set i to forecast pixel values of the image block x, wherein all the movement information units in the merger movement information unit set i are respectively selected from at least a part of the movement information units in the candidate movement information unit sets corresponding to the different pixel samples in the K1 pixel samples. The image forecasting method and the related device facilitate reduction of computation complexity of image forecasting based on the non-translation movement model.

The invention relates to a color image three-dimensional reconstruction method based on three-dimensional matching, comprising the following steps of: (1) simultaneously and respectively taking an image from proper angles by using two color cameras; (2) respectively calibrating the internal parameter matrixes and the external parameter matrixes of the two cameras; (3) carrying out polar line correction and image transformation according to calibrated data; (4) working out matching cost for each pixel point in the two corrected images by applying a self-adaption weight window algorithm and acquiring an initial parallax image; (5) marking the reliability coefficient of the pixel initial matching result by adopting matching cost reliability detection and left and right consistency verification; (6) carrying out color segmentation on the images through a Mean-Shift algorithm; (7) carrying out global optimization by a selective confidence propagation algorithm on the basis of color segmentation and pixel reliability classification results to obtain a final parallax image; and (8) working out the three-dimensional coordinates of actual object points on the images according to the calibrated data and the matching relation, thereby reconstructing the three-dimensional point cloud of an object.

The invention discloses a face recognition method based on aggregate loss deep metric learning. The method comprises the steps of 1), preprocessing a training image; 2), performing pre-training on a deep convolutional neural network by means of the preprocessed image, using a softmax loss as a loss function and introducing key point pooling technology; 3), inputting all training images into a pre-trained model, and calculating the initial kind center of each kind; 4), performing fine adjustment on the pre-trained model by means of the aggregate loss, aggregating the samples of the same kind to the kind center through iteratively updating a network parameter and the kind center, and simultaneously increasing distances between different kind centers, thereby learning robust discriminative face characteristic expression; and 5), in application, performing preprocessing on the input image, and respectively inputting the input image into the trained network model for extracting characteristic expression, and realizing face recognition through calculating similarity between different faces. The face recognition method can realize relatively high face recognition accuracy just through training small mass of data.

A system and method for identifying when an indicated or predetermined media transcoding process results in a media stream that is compliant with an indicated interoperability point. Various embodiments allow for the encoding, storage, transcoding, and transmission of a media stream, for which a transcoding process is identified and the resulting media stream of the transcoding process is associated with at least one property. The signaling of the property or properties, and an identification of the transcoding process in one embodiment, may be included in the media bitstream, in a file format container containing the media bitstream, or in a transmission or control protocol for transmission or control of the media bitstream.

The present invention provides a tracking system in which a mobile tag having an unknown position, which tag is to be tracked in space over time, transmits a signal comprising a pair of tones at different frequencies. The transmitted signal is received at each of three receivers, each having a known location, where the phase of each of the tones within the signal is measured. The measured phases are passed to a processing unit which determines the position of the tag at the time of transmission of the signal on the basis of the difference between the measured phases of the two tones. The tracking system operates over a defined finite range to track the position of the mobile tag uniquely in space.

The invention relates to methods and units supporting a multichannel audio extension. In order to allow an efficient extension requiring a low computational complexity, it is proposed that at an encoding end, at least state information is provided as side information for a provided mono audio signal (M) generated out of a multichannel audio signal. The state information indicates for each of a plurality of frequency bands how a predetermined or equally provided gain value is to be applied in the frequency domain to the mono audio signal (M) for obtaining first and a second channel signals (L,R) of a reconstructed multichannel audio signal.

The invention discloses a high-efficiency video coding (HEVC) inter-frame mode judging method based on temporal relativity, which comprises the steps of forecast method configuration and forecast mode selection. The forecast mode selection adopts the temporal relativity between two adjacent frames; the similarity of PU (Physical Unit) modes of a large size CU (Control Unit) of a corresponding piece in the previous frame and a small size CU in the current piece is analyzed according to the relativity; and finally, a PU mode selection method of the current CUs in various dimension is designed for the corresponding pieces in various dimensions according to the similarity. Compared with the HEVC standard in the prior art, with the adoption of the HEVC inter-frame mode judging method, the complexity of codding computation is reduced to a greater extent on the premise that the bit rate and video quality are almost unchanged.

The invention discloses a method for detecting code similarity based on semantic analysis of a program source code, which relates to computer program analyzing technology and a method for detecting complex codes of computer software. The method solves the prior problems of low similarity detection accuracy and high computing complexity on the codes of different syntactic representations and similar semantemes, and also solves the problem of incapability of realizing large-scale program code similarity detection. The method comprises the following steps: resolving two segments of source codes to be detected into two control dependence trees of a system dependence graph respectively and executing basic code standardization respectively; utilizing a measure method to extract candidate similar code control dependence trees of the control dependence trees which are subjected to the basic code standardization; executing an advanced code standardization operation on extracted candidate similar codes; and computing semantic similarity to obtain a similarity result so as to finish the code similarity detection. The method is applied to source code piracy detection, software component library query, software defect detection, program comprehension and the like.