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A Feature Point Matching Based on Spatial Order Constraints Bilateral-Neighbor Vote
Feature point matching is a fundamental and challenging problem in many computer vision applications. In this paper, a robust feature point matching algorithm named spatial order constraintsExpand
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Spatial-Temporal Data Augmentation Based on LSTM Autoencoder Network for Skeleton-Based Human Action Recognition
Data augmentation is known to be of crucial importance for the generalization of RNN-based methods of skeleton-based human action recognition. Traditional data augmentation methods artificially adoptExpand
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Instance Enhancing Loss: Deep Identity-Sensitive Feature Embedding for Person Search
Person search, which is vital for intelligent surveillance, aims at detecting and re-identifying pedestrians from whole monitoring images. However, due to the inaccurate pedestrian detections andExpand
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3D action recognition using multi-temporal skeleton visualization
Action recognition using depth sequences plays important role in many fields, e.g., intelligent surveillance, content-based video retrieval. Real applications require robust and accurate actionExpand
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Joint Dynamic Pose Image and Space Time Reversal for Human Action Recognition from Videos
Human action recognition aims to classify a given video according to which type of action it contains. Disturbance brought by clutter background and unrelated motions makes the task challenging forExpand
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Improved Hash Functions for Cancelable Fingerprint Encryption Schemes
Abstract In order to solve the prealignment problem, this paper constructs new fingerprint features which will not change along with the rotation of fingerprint image. And then the SHA1 algorithm isExpand
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Sample Fusion Network: An End-to-End Data Augmentation Network for Skeleton-Based Human Action Recognition
Data augmentation is a widely used technique for enhancing the generalization ability of deep neural networks for skeleton-based human action recognition (HAR) tasks. Most existing data augmentationExpand
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Infrared-Visible Image Fusion Based on Convolutional Neural Networks (CNN)
Image fusion is a process of combing multiple images of the same scene into a single image with the aim of preserving the full content information and retaining the important features from each ofExpand
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A bidirectional adaptive bandwidth mean shift strategy for clustering
The bandwidth of a kernel function is a crucial parameter in the mean shift algorithm. This paper proposes a novel adaptive bandwidth strategy which contains three main contributions. (1) TheExpand
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Bi-directional Exponential Angular Triplet Loss for RGB-Infrared Person Re-Identification
RGB-Infrared person re-identification (RGB-IR Re-ID) is a cross-modality matching problem with promising applications in the dark environment. Most existing works use Euclidean metric basedExpand
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