1122 results about "Template matching" patented technology

An object detector, an object detecting method and a robot can reduce diction errors of detecting wrong objects without increasing the volume of the computational operation to be performed to detect the right object. A face detector 101 comprises a face detecting section 110 that operates like a conventional face detecting section and is adapted to roughly select face candidates from an input image by template matching and detect face candidates by means of a support vector machine for face recognition, a non-face judging section 120 that detects non-face candidates that are judged to be non-faces and removes them from the face candidates selected by the face detecting section 110 and a skin tracker section 114 for tracking a face region after the non-face judgment. When the assumed distance between the face detector and the face as computed from the input image and the measured distance as measured by a distance sensor show a large difference, when the color variance of the face candidate is small, when the occupancy ratio of the skin color region is large and when the change in the size of the face region is large after the elapse of a predetermined time, the non-face judging section 120 judges such face candidates as non-faces and removes them from the face candidates.

The present invention relates to a video coding method. Specifically, the invention relates to motion vector (MV) coding, wherein the MV coding is based on edge matching or adaptive template matching, namely the motion vector coding based on boundary matching (MVCBM) and the motion vector coding based on adaptive template matching (MVCATM). Generally speaking, the invention limits a prediction candidate set, wherein a predictor adaptively changes based on the current distribution of the adjacent MV. Subsequently, a matching technique (boundary matching in MVCBM and adaptive template matching in MVCATM) is used for reducing the number of the prediction and reducing the number of bits used by indexing. Afterwards, an optimal motion vector predicator is selected from the reduced concentrated predictor. The guessing strategy based on the least MVD standard further saves the number of indexing bits.

The invention discloses a mapping knowledge domain questioning and answering system and method based on a template matching technique. The system comprises an offline module and an online module, wherein the offline module is mainly used for offline data preparation, and the online module is mainly used for system service. The system can support a friendly natural language question of a user to serve as a query, grammatical analysis is conducted on the question of the user, an offline-defined manual template library is searched for a matched question template according to a result obtained through grammatical analysis, a final structurized mapping knowledge domain query statement is generated according to an entity matching method and a relation matching method, retrieving is conducted in a mapping knowledge domain according to the structurized query statement, and then a final result is returned. According to the mapping knowledge domain questioning and answering system and method based on the template matching technique, the precise retrieving result can be given for the question of the user, and the searching satisfaction degree of the user is improved.

Techniques and systems are provided for deriving one or more sets of affine motion parameters at a decoder. For example, the decoder can obtain video data from an encoded video bitstream. The video data includes at least a current picture and a reference picture. The decoder can determine a set of affine motion parameters for a current block of the current picture. The set of affine motion parameters can be used for performing motion compensation prediction for the current block. The set of affine motion parameters can be determined using a current affine template of the current block and a reference affine template of the reference picture. In some cases, an encoder can determine a set of affine motion parameters for a current block using a current affine template of the current block and a reference affine template of the reference picture, and can generate an encoded video bitstream that includes a syntax item indicating template matching based affine motion derivation mode is to be used by a decoder for the current block. The encoded video bitstream may not include any affine motion parameters for determining the set of affine motion parameters.

A system and method is provided for efficiently adapting information content for an electronic device. A normalizer includes a template normalizer for matching and applying a document tree to a template tree, and applying changes to the document tree. If the template normalizer does not find an appropriate template match, an automatic normalizer is utilized. The automatic normalizer utilizes weighting heuristics and pattern recognition with formatting rules to partition content into folders. The automatic normalizer can also utilize embedded normalization markup in the information content to assist in normalizing the information content. Information content can be represented by document object tree. A document object tree is created by storing information relating to the information content into arrays. The stored information describes a document object tree structure and tree dependencies as a mutable object.

Simultaneous tracking of multiple objects in a sequence of video frames captured by multiple cameras may be accomplished by extracting a foreground elements from a background in a frame, segmenting objects from the foreground surface, tracking objects within the frame, globally tracking positions of objects over time across multiple frames, fusing track data of objects obtained from multiple cameras to infer object positions, and resolving conflicts to estimate most likely object positions over time. Embodiments of the present invention improve substantially over existing trackers by including a technique for extraction of the region of interest that corresponds to a playing field, a technique for segmenting players from the field under varying illuminations, a template matching criteria that does not rely on specific shapes or color coherency of objects but on connected component properties, and techniques for reasoning about occlusions and consolidating tracking data from multiple cameras.

The invention relates to a movement human abnormal behavior identification method based on template matching, which mainly comprises the steps of: video image acquisition and behavior characteristic extraction. The movement human abnormal behavior identification method is a mode identification technology based on statistical learning of samples. The movement of a human is analyzed and comprehended by using a computer vision technology, the behavior identification is directly carried out based on geometric calculation of a movement region and recording and alarming are carried out; the Gaussian filtering denoising and the neighborhood denoising are combined for realizing the denoising, thereby improving the independent analysis property and the intelligent monitoring capacity of an intelligent monitoring system, achieving higher identification accuracy for abnormal behaviors, effectively removing the complex background and the noise of a vision acquired image, and improving the efficiency and the robustness of the detection algorithm. The invention has simple modeling, simple algorithm and accurate detection, can be widely applied to occasions of banks, museums and the like, and is also helpful to improve the safety monitoring level of public occasions.

An apparatus and a method for identifying fusion beats as part of an automatic capture routine in a cardiac stimulation device are disclosed. By requiring each post-pulse electrical response to be closely correlated with an expected morphology for either a capture condition or a loss-of-capture condition before classification of the post-pulse electrical response as either capture or loss-of-capture respectively, the present invention is able to identify fusion beats. In various embodiments, this fusion identification is performed using both template matching and assessment of particular detection features. Moreover, in one embodiment, a moving average and a standard deviation are maintained for each detection feature, thereby creating an automatically adjusting evoked response detection threshold.

A camera based position recognition system for a road vehicle. The environment in the direction of travel of the vehicle is acquired by a camera. Using the acquired image data, the position of the vehicle in its environment is determined with regard to an optical signature identified in the obtained image data. For determining the position of the vehicle, use is made of the knowledge of the relationship between the environment coordinate system of the optical signature and that of the camera coordinate system. In simplified manner, position determination occurs with regard to the optical signature on the basis of a template matching imposed on the image data. For this, a template or an optical signature recorded in memory is superimposed on the optical signature identified in the image data in the environment of the vehicle (template matching). From the parameters of this template matching (for example linear compression and rotation parameters) recognizing the existing coordinate system, the position of the vehicle relative to the optical signature can be directly deduced.

The invention discloses a three-dimensional reconstruction method based on coding structured light, comprising the following steps: 1) projecting structured light to an object to be measured, and capturing an image modulated by the object to be measured by a camera; 2) matching an optical template, comprising: (2.1) positioning the optical strip boundary, scanning along each row of the image, determining a pixel point with strong gray variation as a candidate marginal point, and searching a local domain; and (2.2) matching the optical strip: adopting a color cluster method to build a color matching proper vector, comparing image color with a projected color, and defining Euclidean distance between the color proper vector and the cluster center to distribute the colors of red, green, blue and white of the candidate optical strip; and 3) using a calibrated system parameter for three-dimensional reconstruction of the object to be measured, determining the relation between a space point coordinate and the image coordinate point thereof by the calibrated conversion matrix parameter; and restoring three-dimensional spatial coordinate from the image coordinate of a feature point. The invention can simplify calculation process and has high matching precision and high reconstruction precision.

The invention discloses a face detection and recognition method based on skin color segmentation and template matching. A face is segmented with the use of a face skin mixing Gauss model according to the clustering characteristics of face skin color in an YCbCr color space and a region of which the color is close to face skin color is separated from an image so as to achieve the purpose of quickly detecting the outer face of a face. A light compensation technology is used to overcome the influence of brightness on face detection and recognition. Adaptive template matching is used to overcome the influence of a skin-color-alike background on face detection and recognition. A secondary matching algorithm is adopted to reduce the amount of computation during the matching process, and singular value features of a face image are extracted to recognize a face and achieve the purpose of reducing the number of dimensions of a characteristic value matrix in the process of face feature extraction. The face detection and recognition method can quickly detect a face, improves the accuracy of face detection and recognition, is strong in practicability and has strong popularization and application values.

An authentication system includes a mobile device carried by a user and a sensor sensing the user's biometric information. The mobile device includes a template storage unit storing the user's biometric information as a template, a first mutual authentication unit performing mutual authentication with the sensor via the user's body, and a template transmitter transmitting the stored template to the sensor via the user's body when the sensor is verified as valid. The sensor includes a second mutual authentication unit performing mutual authentication with the mobile device via the user's body, a sensing unit sensing the user's biometric information, a degree-of-match determining unit determining whether the biometric information matches the template, and a control-signal output unit outputting a preset control signal when the mobile device is verified as valid and when the biometric information and the template are determined to match each other.

The invention discloses a passenger abnormal behavior identification method based on a human skeleton sequence, which comprises the following steps: 1) shooting an escalator area monitoring video image by a camera; 2) detecting that passenger face through the SVM and trac the passenger face with the KCF to obtain the passenger motion trajectory in the escalator; 3) extracting that human skeleton from the image by using the OpenPose depth learn network; 4) matching that human skeleton to the corresponding passenger trajectory to construct the human skeleton sequence of the passenger; 5) detecting that abnormal behavior skeleton sequence from the passenger human skeleton sequence through template match; 6) using DTW to match it with various abnormal behavior skeleton sequence template to identify abnormal behavior. That invention can accurately and real-time identify a plurality of abnormal behavior of passengers in the escalator base on human skeleton sequence, according to the abnormalbehavior type to control the operation situation of the escalator, and avoid the occurrence of safety accident.

The invention belongs to the technical field of the pattern identification and image processing, and relates to a license plate detection and identification method based on the maximum stable extremal region, which comprises the following steps: extracting the maximum stable extremal region (MSER) to obtain text regions of candidate license plates; adopting one effective feature for description of each extremal region, classifying the extremal regions into 'text' regions and 'non-text' regions with a classifier obtained in prior training, and extracting a license plate from original images based on the characteristics of the structure of the license plate; and describing with the characteristics of the shape context, and completing the character identification through template matching. Since the maximum stable extremal region has the affine invariance, high stability and multi-scale features, and the regions are determined only according to the gray value and are not light-sensitive,the license plate detection and identification method with the maximum stable extremal region as the base is applicable to the complex background, and has the advantages of good stability and high identification rate.

Systems and methods for tracking human hands using parts based template matching within bounded regions are described. One embodiment of the invention includes a processor; an image capture system configured to capture multiple images of a scene; and memory containing a plurality of templates that are rotated and scaled versions of a finger template. A hand tracking application configures the processor to: obtain a reference frame of video data and an alternate frame of video data from the image capture system; identify corresponding pixels within the reference and alternate frames of video data; identify at least one bounded region within the reference frame of video data containing pixels having corresponding pixels in the alternate frame of video data satisfying a predetermined criterion; and detect at least one candidate finger within the at least one bounded region in the reference frame of video data.

The invention provides a vehicle license plate recognition method based on a video. According to the vehicle license plate recognition method based on the video, moving vehicles are detected and separated out with the vehicle video which is obtained through actual photographing by means of a camera serving as input, the accurate position of a vehicle license plate area is determined by conducting vertical edge extraction on a target vehicle image obtained after pre-processing, a vehicle license plate image is separated out, color correction, binaryzation and inclination correction are conducted on a vehicle license plate image, each character in the positioned vehicle license plate area is separated to serve as an independent character, feature extraction is conducted one each character, obtained feature vectors are classified through a classifier which is well trained in advance, a classification result serves as a preliminary recognition result, secondary recognition is conducted on the stained vehicle license plate characters according to a template matching algorithm imitating the visual characteristics of human eyes, and then a final vehicle license plate recognition result is obtained. The vehicle license plate recognition method based on the video has the advantages that hardware cost is reduced, the management efficiency of an intelligent transportation system is improved, the anti-jamming performance and the robustness are high, the recognition efficiency is high, and the recognition speed is high.

A coin identification method and apparatus capable of reliably acquiring stable two-dimensional images of both surfaces of coins 217, and using the acquired two-dimensional images to perform identification and discrimination, reliably and at high speed, between coin denomination, types, dates and origins of mint. In a coin pathway, imaging devices 207a,b are positioned at an image-capture position such that images above and below the surface of passing coins are captured under illumination. The coin denomination is identified by geometric measurements of enhanced images, the coin type is identified by matching templates to enhanced images, and the coin date and mint are identified using template matching to segmented sub-images. In one embodiment, the coin identification information is used for the promotion of a coin counting service. The results are displayed in an entertaining and engaging manner.

The invention discloses a workpiece apparent defect detection method based on machine vision. Firstly, a visual system is used for guiding a robot, the pose of a target workpiece is precisely positioned according to a template matching algorithm based on a gray value, and then workpiece apparent defect detection is carried out and comprises the steps that firstly, a workpiece image is acquired and pretreated through median filtering; secondly, the target workpiece is divided through a global threshold value, and workpiece pose correction is carried out; thirdly, burr interference of the edge of the workpiece is removed through mathematical morphology open operation; fourthly, notches, material sticking, cracking, indentation, needle eyes, scratches and foaming apparent defects are detected. The method solves the problems that the artificial detection speed is slow, the efficiency is low and precision is poor; the problems that according to current vision detection, defect types are singular, the imaging quality is poor, and the false drop rate is high are solved, and the automation degree of precise workpiece production and product quality are improved.

A template matching module is configured to program a processor to apply multiple differently-tuned object detection classifier sets in parallel to a digital image to determine one or more of an object type, configuration, orientation, pose or illumination condition, and to dynamically switch between object detection templates to match a determined object type, configuration, orientation, pose, blur, exposure and/or directional illumination condition.

The invention relates to a multiple-template matching identity recognition method based on an ECG (Electrocardiogram) under an electrocardiogram abnormality state, and belongs to the technical field of biological characteristic identity recognition. The ECG data of a user to be recognized is compared with the data of a registered user in a template library to obtain an identity recognition result. The key technology of the method comprises the following steps: carrying out electrocardiosignal preprocessing for eliminating noise interference; carrying out electrocardiosignal decomposition to separate an electrocardiogram waveform of each period; carrying out standardized processing for independently achieving standardization on time and amplitude scales; carrying out characteristic extraction: in the step, characteristics are extracted by wavelet transform, and clustering analysis is carried out by an ISODATA (Iterative Self-organizing Data Analysis Techniques Algorithm) so as to construct an ECC template library; and carrying out correlation analysis: in the step, correlation between ECG test data and each template is calculated, an optimal matching template is selected, and finally, an identity recognition result is obtained. The multiple-template matching identity recognition method provided by the invention utilizes the intrinsic electrocardiosignal of a human body to recognize an identity, and the ECG data under the abnormality state is considered.

A neurological profile associated with introversion/extroversion levels, simultaneous visual element processing capability, and/or dynamism processing capability, etc., is determined to select market categories and stimulus material targeted to the particular neurological profile. The neurological profile is determined using information such as user input, user activity, social and environmental factors, genetic and developmental factors, and/or neuro-response data. The neurological profile can be matched with corresponding neurological profile templates to select market categories and stimulus material.

The invention discloses a device and a method for structure-reconstruction-based subcutaneous vein three-dimensional visualization, which can acquire three-dimensional space information of a vein and skin. The method comprises the following steps: step 1, performing parameter calibration for three cameras; step 2, utilizing calibrated cameras to perform parameter calibration for the projector; step 3, utilizing structured light method to realize three-dimensional reconstruction of skin surface; step 4, adopting a template matching method to extract a vein central line in near-infrared images; step 5, adopting a pole line matching method to realize three-dimensional reconstruction of the vein central line; step 6, adopting a light projected method accelerated by a GPU (Graphics Processing Unit) to realize three-dimensional visualization of an opisthenar and the vein on a computer display; finally, simulating to obtain a projected image with the projector as a viewpoint according to the three-dimensional data, and projecting the image to the skin surface to be inspected to realize two-dimensional projected display.

The invention discloses a system and a method for monitoring swimming pool drowning based on the Internet of Things. An RFID (radio frequency identification) tag and a camera are effectively combined to judge drowning events, a pulse monitor is used for acquiring user physiological information, a position detection network and the radio frequency identification tag are used for positioning a swimmer, a server is used for initially judging whether the swimmer is drowned or not according to the physiological information and the position information, and then the camera is invoked to monitor the swimmer. Drowning is accurately judged by means of template matching of monitoring images with a standard behavior database, so that detection efficiency and accuracy of the drowning events are improved effectively, and time for discovering drowners is shortened. Besides, drowning is judged jointly by the physiological information and the monitoring images, and accordingly false alarm rate of the drowning events can be effectively decreased.

A diagnosis target image is input, and a template ROI which is set on an image to divide the area on the image into predetermined areas in anatomical terms, physiological terms, or other scientific terms is read out from a storage unit. A matching processing unit warps the template ROI in correspondence with each diagnosis target image on the basis of the feature information of the diagnosis target image extracted by a feature information extraction unit. This warping is executed until an index indicating the degree of matching between the template ROI and the diagnosis image exceeds a predetermined threshold. The warped template ROI is displayed on a display unit upon being superimposed on the diagnosis image.

The invention proposes an algorithm of video pedestrian face detection and tracking through algorithms of motion object detection and motion object tracking, which pertains to the technical field of pattern recognition. The invention is composed of two main parts of a pedestrian face detection algorithm based on the motion object detection and a pedestrian face tracking algorithm based on the motion object tracking. The invention proposes the pedestrian face detection algorithm based on the motion object detection. The algorithm firstly utilizes a motion analysis method to detect the pedestrian, then calculates the gravity center of the human body and determines the face area according to the gravity center of the human body, and finally utilizes a skin-color model and a template matching method to detect the face in the face area. The invention proposes the pedestrian face tracking algorithm based on the motion object tracking. The algorithm tracks the face of the pedestrian through tracking the pedestrian, thereby effectively avoiding effects on the tracking of the face due to swing, rotation, expression, shelter and other factors of the face of the pedestrian.

The present invention provides a fast high-precision geometric template matching method enabling rotation and scaling functions. According to the method, based on image edge information, with the sub-pixel edge points of a template image adopted as feature points, the tangent directions of the gradient directions of a target image adopted as feature lines, and based on the local extremum points of a similarity value, the similarity and the candidate positions of the template image and the target image are calculated from fine to rough through adopting a Pyramid algorithm and according to a similarity function; and pixel-level positioning accuracy is obtained at the bottommost layer of a Pyramid, the least squares method is adopted to carry out fin adjustment, so that sub-pixel positioning accuracy, higher-precision angle and size scaling accuracy can be achieved. The method can realize fast, stable and high-precision positioning and identification of target images which are moved, rotated, scaled and is partially shielded, and where the brightness of illumination changes, illumination is uneven, and cluttered background exists. The method can be applied to situations which require machine vision to carry out target positioning and identification.

The invention discloses an image processing method for automatic pointer-type instrument reading recognition. The method comprises the following steps: (1) Hough circle detection is carried out on the image, a weighted average method is used for positioning the circle center and the radius of a dial, and a dial region square image is extracted; (2) the image is pre-treated, and a binary thinning image of the instrument pointer is extracted; (3) a central projection method is used for determining a pointer angle; (4) a zero graduation line and full graduation line position templates are extracted, and a range starting point and ending point positions are calibrated; (5) by using template matching, zero graduation line and full graduation line angles are obtained; and (6) according to the pointer angle, the zero graduation line angle and the full graduation line angle, the pointer reading is obtained through calculation. Thus, the problem that the instrument dial position on the acquired image is not fixed as the relative position between a camera and the pointer-type instrument is not fixed can be solved, subjective errors as the reading of the instrument is read manually can be eliminated, the efficiency and the precision can be improved, safety of people is ensured, the application range is wide, and robustness is strong.

The invention belongs to the crossing field of computer vision and intelligent robot, and discloses a new multi-feature multi-sensor method for a mobile robot to track a moving body. The method comprises the following steps: 1, coarsely positioning a body carrying a passive tag around a radio frequency identification (RFID) system by using the RFID system; 2, initially positioning the body in an image by using an adaptive template matching algorithm based on head and shoulder features; 3, accurately positioning the body in the image by using a multi-feature-based mean-shift algorithm; 4, predicting the moving state of the body by using a extended Kalman filter algorithm; 5, screening the acquired target position information by using a double-layer collaboration positioning mechanism; and 6, controlling the robot to move along with the body by using a robot following control algorithm. By the method, bodies with different poses can be tracked, the problem that the tracking is influenced when a target suddenly turns and is shielded is solved, and the robot can accurately, stably and continuously track the moving body.

The invention provides a vehicle license plate recognition method, and relates to a method for image recognition. The method comprises the following steps of preprocessing an image; partitioning a vehicle region according to color and texture characteristics; extracting a remarkable factor graph of a vehicle region diagram; extracting candidate vehicle license plates by an Adaboost classifier based on expanded Harr-like characteristic; determining the position of a real vehicle license plate from the candidate vehicle license plates; partitioning the marked vehicle license plate from the corresponding vehicle region original diagram; carrying out character segmentation according to structural characteristic; and carrying out character recognition based on the improved template matching method. With the method provided by the invention, the defects that the application scene of the traditional vehicle license plate recognition method is relatively single, some traditional vehicle license plate recognition methods are only suitably used for single vehicle license plate recognition of the single scene and difficultly used for multiple-vehicle license plate recognition of multiple scenes, and the recognition rate is easily affected by strong light, haze and weak light environments are overcome.

The embodiment of the invention discloses a prediction coding and decoding method between frames, comprising the steps as follows: a coding end determines the coding type and carries out coding operation by comparing the gained template match movement vector of the current block with the movement vector prediction value; a decoding end receives code streams coming from the coding end and determines the decoding type and carries out the decoding operation by comparing the gained template match movement vector of the current block and the movement vector prediction value. The embodiment of the invention also discloses a coding device and a decoding device used for prediction between frames. The method and the device can save code rate excellently during the prediction process between frames.