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Template Matching

Template matching is a technique that is used to find a subimage or a patch (called the template) within a larger image. The basic idea behind template matching is to slide the template image over the larger image and compare the template to each portion of the larger image to determine the similarity between the template and the corresponding portion of the larger image.

Papers

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Showing 176–200 of 219 papers

TitleStatusHype
A 3D Object Detection and Pose Estimation Pipeline Using RGB-D Images—0
Template Matching with Deformable Diversity SimilarityCode0
Fast and accurate spike sorting of high-channel count probes with KiloSortCode0
Extraction of airway trees using multiple hypothesis tracking and template matching—0
Deep Watershed Transform for Instance SegmentationCode0
Best-Buddies Tracking—0
Template Matching Advances and Applications in Image Analysis—0
Real-Time RGB-D based Template Matching Pedestrian Detection—0
Best-Buddies Similarity - Robust Template Matching using Mutual Nearest Neighbors—0
Pooling Faces: Template based Face Recognition with Pooled Face Images—0
Automatic Techniques for Gridding cDNA Microarray Images—0
Human Computer Interaction Using Marker Based Hand Gesture RecognitionCode0
Humans and deep networks largely agree on which kinds of variation make object recognition harder—0
DTM: Deformable Template Matching—0
A Survey on Object Detection in Optical Remote Sensing Images—0
Template Matching via Densities on the Roto-Translation Group—0
A landmark-based algorithm for automatic pattern recognition and abnormality detection—0
Latent-Class Hough Forests for 6 DoF Object Pose Estimation—0
Peeking Template Matching for Depth Extension—0
Procedural Editing of 3D Building Point Clouds—0
Efficient Discriminative Nonorthogonal Binary Subspace with its Application to Visual Tracking—0
Fast Template Matching by Subsampled Circulant Matrix—0
Fingerprint Recognition Using Translation Invariant Scattering Network—0
Iris Recognition Using Scattering Transform and Textural Features—0
A Novel Hybrid Approach for Cephalometric Landmark Detection—0
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