Person Identification
18 papers with code • 2 benchmarks • 8 datasets
Datasets
11k Hands
iQIYI-VID
NSVA
MotionID: IMU all motions part3
MotionID: IMU specific motion
MotionID: IMU all motions part1
MotionID: IMU all motions part2
Latest papers with no code
Gait Data Augmentation using Physics-Based Biomechanical Simulation
This paper focuses on addressing the problem of data scarcity for gait analysis.
Recognizing People by Body Shape Using Deep Networks of Images and Words
Although the non-linguistic model yielded fewer false accepts at all distances, fusion of the linguistic and non-linguistic models decreased false accepts for all, but the UAV images.
Human Body Pose Estimation for Gait Identification: A Comprehensive Survey of Datasets and Models
We present a detailed review of the human pose estimation and gait analysis that make the skeleton-based approaches possible.
Multi-Channel Time-Series Person and Soft-Biometric Identification
On-body device (OBD) recordings of human movements are often preferred for HAR applications not only for their reliability but as an approach for identity protection, e. g., in industrial settings.
Attribute De-biased Vision Transformer (AD-ViT) for Long-Term Person Re-identification
Person re-identification (re-ID) aims to retrieve images of the same identity from a gallery of person images across cameras and viewpoints.
Online Boosting-Based Target Identification among Similar Appearance for Person-Following Robots
It is challenging for a mobile robot to follow a specific target person in a dynamic environment, comprising people wearing similar-colored clothes and having the same or similar height.
Two-headed eye-segmentation approach for biometric identification
Iris-based identification systems are among the most popular approaches for person identification.
Robust Person Identification: A WiFi Vision-based Approach
In particular, we leverage multiple antennas on next-generation WiFi devices and 2D AoA estimation of the signal reflections to enable WiFi to visualize a person in the physical environment.
Artificial Image Tampering Distorts Spatial Distribution of Texture Landmarks and Quality Characteristics
Advances in AI based computer vision has led to a significant growth in synthetic image generation and artificial image tampering with serious implications for unethical exploitations that undermine person identification and could make render AI predictions less explainable. Morphing, Deepfake and other artificial generation of face photographs undermine the reliability of face biometrics authentication using different electronic ID documents. Morphed face photographs on e-passports can fool automated border control systems and human guards. This paper extends our previous work on using the persistent homology (PH) of texture landmarks to detect morphing attacks. We demonstrate that artificial image tampering distorts the spatial distribution of texture landmarks (i. e. their PH) as well as that of a set of image quality characteristics. We shall demonstrate that the tamper caused distortion of these two slim feature vectors provide significant potentials for building explainable (Handcrafted) tamper detectors with low error rates and suitable for implementation on constrained devices.
Gait Cycle Reconstruction and Human Identification from Occluded Sequences
Gait-based person identification from videos captured at surveillance sites using Computer Vision-based techniques is quite challenging since these walking sequences are usually corrupted with occlusion, and a complete cycle of gait is not always available.
