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Found 12 papers, 3 papers with code
Joint Person Identity, Gender and Age Estimation from Hand Images using Deep Multi-Task Representation Learning
In this paper, we propose a multi-task representation learning framework to jointly estimate the identity, gender and age of individuals from their hand images for the purpose of criminal investigations since the hand images are often the only available information in cases of serious crime such as sexual abuse.
Local-Aware Global Attention Network for Person Re-Identification
We carefully design the Local-Aware Global Attention Network (LAGA-Net), a multi-branch deep network architecture consisting of one branch for spatial attention, one branch for channel attention, one branch for global feature representations and another branch for local feature representations.
Mushrooms Detection, Localization and 3D Pose Estimation using RGB-D Sensor for Robotic-picking Applications
In case of missing depth information at the detected center of each mushroom, we estimate from the nearest available depth information within the radius of each mushroom.
Multi-Branch with Attention Network for Hand-Based Person Recognition
In this paper, we propose a novel hand-based person recognition method for the purpose of criminal investigations since the hand image is often the only available information in cases of serious crime such as sexual abuse.
Hand-Based Person Identification using Global and Part-Aware Deep Feature Representation Learning
Our proposed method, Global and Part-Aware Network (GPA-Net), creates global and local branches on the conv-layer for learning robust discriminative global and part-level features.
Derivation of a Constant Velocity Motion Model for Visual Tracking
Motion models play a great role in visual tracking applications for predicting the possible locations of objects in the next frame.
Occlusion-Robust Online Multi-Object Visual Tracking using a GM-PHD Filter with CNN-Based Re-Identification
We propose a novel online multi-object visual tracker using a Gaussian mixture Probability Hypothesis Density (GM-PHD) filter and deep appearance learning.
Large-Scale Person Re-Identification
Multiple Object Tracking
+1
Robust Online Multi-target Visual Tracking using a HISP Filter with Discriminative Deep Appearance Learning
We propose a novel online multi-target visual tracker based on the recently developed Hypothesized and Independent Stochastic Population (HISP) filter.
Large-Scale Person Re-Identification
Multiple Object Tracking
+1
Development of a N-type GM-PHD Filter for Multiple Target, Multiple Type Visual Tracking
We propose a new framework that extends the standard Probability Hypothesis Density (PHD) filter for multiple targets having $N\geq2$ different types based on Random Finite Set theory, taking into account not only background clutter, but also confusions among detections of different target types, which are in general different in character from background clutter.
Long-term Correlation Tracking using Multi-layer Hybrid Features in Sparse and Dense Environments
In this paper, we propose a new long-term visual tracking algorithm, learning discriminative correlation filters and using an online classifier, to track a target of interest in both sparse and crowded video sequences.
MRI-PET Registration with Automated Algorithm in Pre-clinical Studies
Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) automatic 3-D registration is implemented and validated for small animal image volumes so that the high-resolution anatomical MRI information can be fused with the low spatial resolution of functional PET information for the localization of lesion that is currently in high demand in the study of tumor of cancer (oncology) and its corresponding preparation of pharmaceutical drugs.
Multiple Target, Multiple Type Filtering in RFS Framework
First, we extend the standard Probability Hypothesis Density (PHD) filter for multiple type of targets, each with distinct detection properties, to develop multiple target, multiple type filtering, N-type PHD filter, where $N\geq2$, for handling confusions among target types.
Applications
