Abstract: Embodiments are disclosed for finding similar persons in images. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an image query, the image query including an input image that includes a representation of a person, generating a first cropped image including a representation of the person's face and a second cropped image including a representation of the person's body, generating an image embedding for the input image by combining a face embedding corresponding to the first cropped image and a body embedding corresponding to the second cropped image, and querying an image repository in embedding space by comparing the image embedding to a plurality of image embeddings associated with a plurality of images in the image repository to obtain one or more images based on similarity to the input image in the embedding space.

Abstract: Methods for determining metrology sites for products includes detecting corresponding objects in measurement data of one or more product samples, and aligning the detected objects are aligned. The methods also include analyzing the aligned objects, and determining metrology sites based on the analysis. Devices use such methods to determine metrology sites for products.

Abstract: The present invention relates to a pattern edge detection method applicable to a semiconductor inspection apparatus that performs a pattern inspection using pattern design data. This method includes: generating an image of a pattern; detecting an edge of the pattern on the image based on a reference pattern generated from design data for the pattern; repeating generating of an image of a pattern and detecting of an edge of the pattern on the image to produce training-data candidates including a plurality of images and corresponding pattern edges; determining training data by removing pattern edges and corresponding images from the training-data candidates, the pattern edges to be removed being pattern edges satisfying a predetermined disqualification condition; producing an edge detection model by machine learning using the training data; generating an image of other pattern; and detecting an edge of the other pattern on the image using the edge detection model.

Abstract: A method implemented on a visual computing device to authenticate one or more users includes receiving a first three-dimensional pattern from a user. The first three-dimensional pattern is sent to a server computer. At a time of user authentication, a second three-dimensional pattern is received from the user. The second three-dimensional pattern is sent to the server computer. An indication is received from the server computer as to whether the first three-dimensional pattern matches the second three-dimensional pattern within a margin of error. When the first three-dimensional pattern matches the second three-dimensional pattern within the margin of error, the user is authenticated at the server computer. When the first three-dimensional pattern does not match the second three-dimensional pattern within the margin of error, user is prevented from being authenticated at the server computer.

Abstract: A computing system receives from a media presentation device a query fingerprint stream representing media content being presented by the media presentation device, where the query fingerprint stream has been determined to represent a first channel. The computing system then detects that a threshold mismatch exists between the received query fingerprint stream and a reference fingerprint stream representing the first channel, thus indicating a likelihood that the media presentation device has transitioned from presenting the first channel to presenting a second channel. Responsive to detecting the threshold mismatch, the system thus discontinues channel-specific action with respect to the first channel. For instance, the system could discontinue superimposing of first-channel-specific content on the presented media content and perhaps start superimposing of second-channel-specific content instead.

Abstract: The present invention relates to a display device and a method for image processing thereof, in which an input image is enlarged and a part of the enlarged image is selected as an image to be displayed on the screen of a display panel, and it is possible to thereby prevent screen burn-in and to prevent a phenomenon in which pixel data is not present and thus a pixel appears black when an image is moved on the screen.

Abstract: The present application discloses a video-based human behavior recognition method, apparatus, device and storage medium, and relates to the technical field of human recognitions. The specific implementation scheme lies in: acquiring a human rectangle of each video frame of the video to be recognized, where each human rectangle includes a plurality of human key points, and each of the human key points has a key point feature; constructing a feature matrix according to the human rectangle of the each video frame; convolving the feature matrix with respect to a video frame quantity dimension to obtain a first convolution result and convolving the feature matrix with respect to a key point quantity dimension to obtain a second convolution result; inputting the first convolution result and the second convolution result into a preset classification model to obtain a human behavior category of the video to be recognized.

Abstract: A multi-label object detection method based on an object detection network includes: selecting an image of an object to be detected as an input image; based on a trained object detection network, obtaining a class of the object to be detected, coordinates of a center of the object to be detected, and a length and a width of a detection rectangular box according to the input image; and outputting the class of the object to be detected, the coordinates of the center of the object to be detected, and the length and the width of the detection rectangular box. The method of the present invention can perform real-time and accurate object detection on different classes of objects with improved detection speed and accuracy, and can solve the problem of object overlapping and occlusion during the object detection.

Abstract: In some implementations, a device may detect edges in an image, and may identify, based on the edges, a rectangle that bounds a document in the image. The device may detect lines in the image, and may identify edge candidate lines by discarding one or more of the lines. The device may identify intersection points where lines, included in the edge candidate lines, intersect with one another. The device may identify corner candidate points by discarding one or more points included in the intersection points, and may identify a corner point included in the corner candidate points. The corner point may be a point, included in the corner candidate points, that is closest to one corner of the bounding rectangle. The device may perform perspective correction on the image of the document based on identifying the corner point.

Abstract: Example systems disclosed herein are to process image frames with a reverse image search engine to generate corresponding search results pages, capture screenshots corresponding respectively to the search results pages, generate base query records corresponding to respective ones of the screenshots that have respective textual information that matches a base search term, the respective ones of the base query records including the base search term and at least portions of the respective textual information from the corresponding screenshots, determine an object search term based on a frequency analysis of the textual information included in the base query records, generate object query records corresponding respectively to ones of the base query records that have respective textual information matching the object search term, and identify a first object depicted in the video based on at least one criteria applied to the object query records.

Abstract: An input action setting unit selects an action of a user to be accepted as an input operation. An input accepting unit accepts an output from a sensor that is worn by a user and detects a movement of at least one region of the user. When detecting based on the output of the sensor that the user has performed the action selected by the input action setting unit, the input accepting unit accepts the action as an input operation performed by the user. The input action setting unit selects an action of the user to be accepted as the input operation from among preset multiple kinds of action of the user based on at least one of an environment in which the user is placed and a working action of the user other than the input operation, and sets the action in the input accepting unit.

Abstract: Methods and systems including: applying a gamma adjustment to frames of an input video with particular values of parameters to generate at least one set of gamma-adjusted frames to generate at least one set of gamma-adjusted frames; applying a segmentation technique to the at least one set of gamma-adjusted frames to generate segmentation masks; applying an optical flow technique to the at least one set of the gamma-adjusted frames to generate optical flow maps; and combining the segmentation masks and the optical flow maps to generate hybrid segmentation masks.

Abstract: The described technology is generally directed towards comparing two images for content differences, such as images based on the frames of a show and a derivative version of that show. Frame pairs such as from an original show and its derivative version are processed into image pairs, which can include decoding, scaling, luminance extraction and/or filtering. An edge pixel image is obtained via edge detection for each image. Edge pixels in one image are compared against a counterpart edge pixel (and possibly neighboring pixels) in the other image to determine matches (matching edge pixels) and mismatches. An image with too many errors based on the mismatches is deemed as a candidate for further review. A difference image can be generated to assist a reviewer in detecting where the mismatches were detected. By repeating for the various frames, a show can be automatically compared against its derivative for content differences.

Abstract: The present disclosure discloses a method and an apparatus for generating a map, relating to a field of intelligent transportation technologies in the field of computer technologies. The method includes the following. A street view image corresponding to a target road is obtained. The street view image is input into a preset deep learning model to obtain data of a candidate isolation belt corresponding to the street view image. The data of the candidate isolation belt includes information of the candidate isolation belt and a probability corresponding to the information of the candidate isolation belt. The information of the candidate isolation belt is corrected based on a preset correction strategy and the probability to obtain information of a target isolation belt. An icon corresponding to the information of the target isolation belt is added on a base map including the target road to generate a map.

Abstract: A method for determining a presence of an occupant within a vehicle includes capturing, via a driver facing camera, video image data, including a plurality of image frames of a field-of-view of the driver facing camera. At least one area-of-interest within the image frames is defined, and a foreground pixel count of each image frame of each area-of-interest is determined. At each Nth image frame, an occupancy for each area of interest is determined based at least in part on the foreground pixel count. The occupancy indicates whether the occupant is present or absent in the respective area-of-interest. A history of the occupancy determination for each area-of-interest is maintained, and a final status for each area-of-interest is determined based on the respective history of occupancy. External indicators are initiated based on the final status determination.

Abstract: Systems, methods, and non-transitory computer readable media are provided for labeling depictions of objects within images. An image may be obtained. The image may include a depiction of an object. A user's marking of a set of dots within the image may be received. The set of dots may include one or more dots. The set of dots may be positioned within or near the depiction of the object. The depiction of the object within the image may be labeled based on the set of dots.

Abstract: An image object recognition method, apparatus, and computer device are provided. The image object recognition method includes: performing feature extraction in the direction of a horizontal angle of view and in the direction of a vertical angle of view of an image respectively, to extract a lateral feature sequence and a longitudinal feature sequence of the image; fusing the lateral feature sequence and the longitudinal feature sequence to obtain a fused feature; activating the fused feature by using a preset activation function to obtain an image feature; and recognizing an object in the image by decoding the image feature. This solution can improve the efficiency of the object recognition.

Abstract: Described are methods, systems, and medias for detecting spoofing of biometric identity recognition and/or validating an identity recognition match by using the camera of a mobile device, processing the user's face image or set of images at a first and second distance to generate first and second data representations, processing the first data representation into a predictive model, and comparing the data representation with the predictive model.

Abstract: Devices, systems, and methods are provided for testing and validation of a camera. A device may determine a content object placed in a line of sight of a camera device, wherein the content object provides informational and visual content. The device may capture one or more images of the content object. The device may cause an electromagnetic event using an electromagnetic interference device, causing an electromagnetic event to affect an image quality of at least one of the one or more images captured by the camera device. The device may assign a structural similarity index (SSIM) score to the at least one image of the one or more images, wherein the SSIM score indicates a camera validation status of the camera device. The device may assign an SSIM score between on one image taken without the presence of interference and one image taken in the presences of the interference.

Abstract: According to one embodiment, an image processing device includes a hardware processor implemented by one or more processors. The hardware processor acquires a first image of a first object and a second image of a second object which is different from the first object, the images captured by an image capture processing device including an image capturing element and an optical system which images an object image on an image capturing surface of the image capturing element. The hardware processor measures a point spread function of the optical system based on the first image and the second image.

Abstract: Systems and methods for digital rendering items with designs incorporate therein are disclosed. According to certain aspects, an electronic device may support a design application that may modify a digital image using an identity texture and a texture map, resulting in the modified digital image taking the shape or form of a portion of a digital model of an item. The electronic device may generate a digital rendering of the item using the modified digital image and the digital model of the item, and may enable a user to review the digital rendering and/or place an order for a physical version of the item according to the digital rendering.

Abstract: An image recognition method and apparatus are provided. The method includes: acquiring a first brightness of a target side of an electronic device when an image recognition triggering operation for the electronic device is detected, wherein the electronic device is provided with an image capturing circuit and a light-emitting circuit; controlling the light-emitting circuit to complement the target side with light when the first brightness is less than a preset brightness threshold; controlling the image capturing circuit to capture a target image of the target side during light complement; and recognizing the target image.

Abstract: An endoscope device, an endoscope operation method, and a program are provided. An endoscope device includes a motion pattern identification unit that identifies a single or plurality of motion patterns indicating a specific movement of a scope head of a scope unit, an operation storage unit that stores a single or plurality of pieces of operation information for instructing an operation of the endoscope device, and the single or plurality of motion patterns of the scope head in association with each other, an operation information acquisition unit that acquires the operation information corresponding to the motion pattern from the operation storage unit on the basis of the motion pattern identified by the motion pattern identification unit, and an operation execution unit that executes an operation corresponding to the operation information acquired by the operation information acquisition unit.

Abstract: A method and system for monitoring an e-commerce platform. The system includes a computing device and a visual sensor. The computing device includes a processor and a storage device storing computer executable code. The computer executable code, when executed at the processor, is configured to: extract image keypoints from an image of the object captured by the visual sensor; retrieve a template of the object, where the template includes template keypoints of at least one template side surface of the object; pick two template keypoints from the template side surface and determine two image keypoints respectively matching the two picked template keypoints; build a bounding box of the object based on the two determined image keypoints; and refine the bounding box.

Abstract: Black borders are detected in an image frame using a grey scale image of the image frame, and an edge image of the image frame. Candidate black borders are identified using maximum grey scale values associated with rows and columns of pixels of the grey scale image of the image frame, and then validated using a sum of grey scale values associated with rows and columns of pixels in the edge image of the image frame. If the validation fails, it is presumed that no black border exists.

Abstract: A system and method of detecting objects are provided. The method includes generating first edge information from first image data representing an object based on a first mode of image capture, generating second edge information from second image data representing the object based on a second mode of image capture, the second mode being different from the first mode, fusing the first edge information with the second edge information to generate fused edge information, generating an object detection hypothesis based on the fused edge information, and validating the object detection hypothesis based on the fused edge information, the first edge information, and/or the second edge information.

Abstract: Provided is an image analysis distance information provision system, and the system includes: a computer and an imaging device. The control unit of the computer is configured to perform the following steps according to an image of an object captured by the imaging device: determining the type of the captured object; calculating the actual length of the captured object per unit length of the image of the captured object; calculating the shooting range of the image of the captured object according to the calculation result; and estimating the distance from the imaging device to the captured object according to the calculated shooting range.

Abstract: An image processing device that detects an image of an object from input data captured by a vision sensor, on the basis of a model pattern including a set of a plurality of first feature points representing the shape of the object, includes an object detection unit that detects images of the object by matching between a plurality of second feature points extracted from the input data and a plurality of first feature points forming the model pattern, a corresponding point selection unit that selects, for each image of the object, second feature points corresponding to the first feature points and stores the selected second feature points as corresponding points, and a model pattern correction unit that calculates a statistic of a predetermined physical quantity of the plurality of corresponding points associated with each first feature point and corrects the first feature point on the basis of the statistic.

Abstract: Disclosed are computer-implemented methods, non-transitory computer-readable media, and systems for image processing. One computer-implemented method includes determining a rotated angle of an identification (ID) document image, where the rotated angle corresponds to an angle between a bottom edge of the ID document image and an x-axis. The ID document image is rotated based on the rotated angle, where an angle is defined between the bottom edge of the rotated ID document image and the x-axis, and where a value of the angle is within a predefined range. Image regression is performed on the rotated ID document image to obtain coordinates of four corner points of the rotated ID document image. Image alignment is performed on the rotated ID document image based on the coordinates of four corner points of the rotated ID document image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for monitoring of pet feeding. The methods, systems, and apparatus include actions of: obtaining a first reference image of a container corresponding to a full state of the container; obtaining a second reference image of the container corresponding to an empty state of the container; obtaining a sample image of the container; based on the first and second reference images, determining an amount of content in the container from the sample image; and based on the amount of the content being less than a reference amount, notifying a user that the amount of the content is getting low.

Abstract: An object of the present disclosure is to improve setting accuracy of site regions in brain image data. A brain image data processing apparatus 100 includes: a brain image data reading unit for reading brain image data in which the site regions for identifying each site are set at positions corresponding to each site of a brain; a probability calculation unit for calculating a probability that each pixel is included in each site region based on a distance between each pixel and each site region for each pixel not included in any site region in the brain image data read by the brain image data reading unit; and a determination unit for determining which site region each pixel belongs to, based on the probability calculated by the probability calculation unit.

Abstract: Systems, methods, and non-transitory computer readable media can align face images, classify face images, and verify face images by employing a deep neural network (DNN). A 3D-aligned face image can be generated from a 2D face image. An identity of the 2D face image can be classified based on provision of the 3D-aligned face image to the DNN. The identity of the 2D face image can comprise a feature vector.

Abstract: System, methods, and other embodiments described herein relate to self-supervised training for monocular depth estimation. In one embodiment, a method includes filtering disfavored images from first training data to produce second training data that is a subsampled version of the first training data. The disfavored images correspond with anomaly maps within a set of depth maps. The first depth model is trained according to the first training data and generates the depth maps from the first training data after initially being trained with the first training data. The method includes training a second depth model according to a self-supervised training process using the second training data. The method includes providing the second depth model to infer distances from monocular images.

Abstract: One embodiment of the present invention sets forth a technique for evaluating productive congestion within an architectural space design. The technique includes generating a space analysis graph for the architectural space design. The technique further includes determining a traversal value for at least a first node of a plurality of nodes included in the space analysis graph, determining a centroid of the plurality of nodes, determining a path within the space analysis graph from at least the first node to the centroid, and determining a productive congestion metric based on at least the path from the first node to the centroid and the traversal value of the first node.

Abstract: Methods, apparatus, and computer readable media that are related to 3D object detection and pose determination and that may optionally increase the robustness and/or efficiency of the 3D object recognition and pose determination. Some implementations are generally directed to techniques for generating an object model of an object based on model point cloud data of the object. Some implementations of the present disclosure are additionally and/or alternatively directed to techniques for application of acquired 3D scene point cloud data to a stored object model of an object to detect the object and/or determine the pose of the object.

Abstract: A parking assistance device includes a pair of left and right sonar devices provided in a vehicle, an obstacle detection controller for determining whether an obstacle present within a determination target distance range on a side of the vehicle is a wall or a curb by comparing a level value of a reflection wave received by one of the sonar devices with each of a first threshold value and a second threshold value that are different from each other, and an automatic parking controller for setting a guiding route for automatic parking depending on a determination result, and the automatic parking controller sets the guiding route requiring a large amount of steering of the vehicle in a case where the determination result indicates a curb, compared with a case where the determination result indicates a wall in the automatic parking in the form of parallel parking.

Abstract: In an approach to training image classification models through the creation and utilization of stub images, one or more computer processors tag ground truth data utilizing subject matter expert inputs for a classification. The one or more computer processors extract one or more features and one or more boundaries from the tagged ground truth data. The one or more computer processors tag the one or more extracted features and the one or more extracted boundaries. The one or more computer processors generate one or more stub images by incorporating the one or more tagged features, and the one or more tagged boundaries at a confidence level. The one or more computer processors train a classification model utilizing the one or more generated stub images. The one or more computer processors deploy the trained classification model.

Abstract: A layout of original pattern is rotated in a rotational direction to form a layout of rotation pattern. Vertices and segment points of the layout of rotation pattern are matched with ones of the reference points closest thereto, and the matched reference points are connected to form a layout of first modification pattern. A region of the layout of first modification pattern is enlarged to form a layout of second modification pattern. A layout of reference pattern having the same direction as the layout of rotation pattern is formed. A layout of target pattern is formed based on a region where the layouts of reference pattern and second modification pattern overlap. An optical proximity correction is performed on the layout of target pattern to form a layout of third modification pattern, which is rotated in a reverse rotational direction to form a layout of final pattern.

Abstract: A contour recognition device includes: a projecting unit which projects pattern light; a light quantity adjustment unit which adjusts a light quantity of the pattern light; two photographing units which capture, from different viewpoints, the target and the placement surface; a distance calculation unit which calculates a distance at every two-dimensional position; an image generation unit which generates a distance image which gradient expresses a distance from a maximum distance until a minimum distance at every two-dimensional position; and a contour extraction unit which extracts a contour of the target, in which the light quantity adjustment unit adjusts the light quantity so that the distance of at least the contour of the target cannot be calculated, and the distance of the placement surface can be calculated, and the image generation unit generates an image so that a maximum distance becomes a distance greater than the distance of the placement surface.

Abstract: An abnormality detection device calculates high-dimensional feature values from real world data; projects, by using a matrix generated from real world data collected for learning so as to project the feature values onto an abnormality discriminant space, feature values calculated from real world data which is input for inspection onto an abnormality discriminant space, the abnormality discriminant space being used for determining presence or absence of an abnormality; judges the presence or absence of an abnormality from a distribution in the abnormality discriminant space; identifies, if an abnormality is found and if the abnormality is a known abnormality, the content of the abnormality from a trend of a distribution in the abnormality discriminant space and presenting the content of the abnormality; and visually displays a distribution in the abnormality discriminant space as a detection result of an abnormality.

Abstract: The sharing of signal segments using a semantic understanding of what is included within the signal segment. Upon selection of a physical entity (or portion thereof) that is rendered within a signal segment, the system then extracts portion(s) of signal segment(s) in which that selected physical entity appears. A representation of the extracted signal segment portion are then dispatched to recipients. Thus, portions of signal segments may be shared at the granularity of the content of what the signal segment depicts. There is wide flexibility in what representations of those signal segment portion(s) are shared.

Abstract: A method of de-blocking filtering a processed video is provided. The processed video includes a plurality of blocks and each block includes a plurality of sub-blocks. A current block of the plurality of blocks includes vertical edges and horizontal edges. The processed video further includes a set of control parameters and reconstructed pixels corresponding to the current block. A boundary strength index is estimated at the vertical edges and at the horizontal edges of the current block. The set of control parameters, the reconstructed pixels corresponding to the current block and partially filtered pixels corresponding to a set of adjacent sub-blocks are loaded. The vertical edges and the horizontal edges of the current block are filtered based on the boundary strength index and the set of control parameters such that a vertical edge of the current block is filtered before filtering at least one horizontal edge of the current block.

Abstract: A method of characterising particles (140) by using a processor (301) to identify a particle boundary (165) of at least one particle (140) in an image (135, 171). The method comprises processing the image (135, 171) using a thresholding method to determine a first boundary (160a) corresponding with the at least one particle (140) and processing the image (135, 171) using an edge detection method to determine a second boundary (160b) corresponding with at the least one particle (140). The first boundary (160a) and second boundary (160b) are combined to create a combined boundary (160). A particle boundary (165) of the at least one particle (140) is determined using the combined boundary. A parameter used by the edge detection method is adaptive, and determined with reference to the image (135, 171).

Abstract: A method and system displaying and managing images of consumer products with audio commands and responses. One or more consumer products are selected with target network device with a target audio interface. An N-layer digital image is created that includes an M-layer hierarchy of vector images and/or visual overlays in progressive resolution format and allows progressive resolution display without loss of image quality on the selected plural consumer products that appear in the N-layer digital image. Consumer products are selected with audio commands and audio responses from the target network device via audio commands sent and received on the target audio interface. Consumer products selected with audio commands are placed in a graphical shopping cart/bag that provides progressive resolution display directly from the graphical shopping cart/bag and allows new or different consumer products to be selected directly from the graphical shopping cart/bag via audio commands and responses.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle and, for only those agents which are high priority agents, generating data characterizing the agents using a first prediction model. In a first aspect, a system identifies multiple agents in an environment in a vicinity of a vehicle. The system generates a respective importance score for each of the agents by processing a feature representation of each agent using an importance scoring model. The importance score for an agent characterizes an estimated impact of the agent on planning decisions generated by a planning system of the vehicle which plans a future trajectory of the vehicle. The system identifies, as high-priority agents, a proper subset of the plurality of agents with the highest importance scores.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle. In one aspect, a method comprises processing an input that characterizes a trajectory of the vehicle in an environment using an importance scoring model to generate an output that defines a respective importance score for each of a plurality of agents in the environment in the vicinity of the vehicle. The importance score for an agent characterizes an estimated impact of the agent on planning decisions generated by a planning system of the vehicle which plans a future trajectory of the vehicle. The high-priority agents are identified as a proper subset of the plurality of agents with the highest importance scores.

Abstract: The present disclosure relates to a method and a system for standardizing a hemodynamics measurement result and a non-transitory computer-readable recording medium. According to one aspect of the present disclosure, provided is a method for standardizing a measurement result obtained from a device for monitoring hemodynamics, the method comprising the steps of: capturing an image of a subject wearing a monitoring device; defining a photogrammetric coordinate system on the captured image, and converting a preset local coordinate system on the monitoring device into the photogrammetric coordinate system; and converting the photogrammetric coordinate system into a standard coordinate system which is based on a standard space.

Abstract: A method for providing a dynamic loupe in a window of an electronic device. The method includes displaying a document in the window of the electronic device, displaying, using at least dimensions associated with a first sub-region of the document being displayed, the dynamic loupe for the first sub-region, receiving an instruction to associate the dynamic loupe with a second sub-region of the document being displayed, determining one or more dimensions of the second sub-region, and displaying, using at least the identified one or more dimensions, the dynamic loupe for the second sub-region.

Abstract: Embodiments provide for cut-aware UV transfer. Embodiments include receiving a surface correspondence map that maps points of a source mesh to points of a target mesh. Embodiments include generating a set of functions encoding locations of seam curves and wrap curves from a source UV map of the source mesh. Embodiments include using the set of functions and the surface correspondence map to determine a target UV map that maps a plurality of target seam curves and a plurality of target wrap curves to the target mesh. Embodiments include transferring a two-dimensional parametrization of the source UV map to the target UV map.

Abstract: An advanced driver assistance system (ADAS) and method for a vehicle utilize a light detection and ranging (LIDAR) system configured to emit laser light pulses and capture reflected laser light pulses collectively forming three-dimensional (3D) LIDAR point cloud data and a controller configured to receive the 3D LIDAR point cloud data, convert the 3D LIDAR point cloud data to a two-dimensional (2D) birdview projection, obtain a template image for object detection, the template image being representative of a specific object, blur the 2D birdview projection and the template image to obtain a blurred 2D birdview projection and a blurred template image, and detect the specific object by matching a portion of the blurred 2D birdview projection to the blurred template image.