Visual Appearance Based Person Retrieval in Unconstrained Environment Videos

2019-10-31 · Hiren Galiyawala, Mehul S. Raval, Shivansh Dave

Visual appearance-based person retrieval is a challenging problem in surveillance. It uses attributes like height, cloth color, cloth type and gender to describe a human. Such attributes are known as soft biometrics. This paper proposes person retrieval from surveillance video using height, torso cloth type, torso cloth color and gender. The approach introduces an adaptive torso patch extraction and bounding box regression to improve the retrieval. The algorithm uses fine-tuned Mask R-CNN and DenseNet-169 for person detection and attribute classification respectively. The performance is analyzed on AVSS 2018 challenge II dataset and it achieves 11.35% improvement over state-of-the-art based on average Intersection over Union measure.

📄 PDF Abstract BibTeX arXiv:1910.14565

Code (0)

등록된 구현이 없습니다.

Tasks

AttributeHuman DetectionPerson Retrieval regression Retrieval

Methods 이 논문이 사용한 방법론

RPN A Region Proposal Network, or RPN, is a fully convolutional network that simultaneously predicts object bounds and objectness scores at each position. The RPN is trained…

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…

RoIAlign Region of Interest Align, or RoIAlign, is an operation for extracting a small feature map from each RoI in detection and segmentation based tasks. It removes the harsh…

Mask R-CNN Mask R-CNN extends Faster R-CNN to solve instance segmentation tasks. It achieves this by adding a branch for predicting an…

SA-Person: Text-Based Person Retrieval with Scene-aware Re-ranking

2025-05-30 · Yingjia Xu, Jinlin Wu, Zhen Chen, Daming Gao 외

Text-based person retrieval aims to identify a target individual from a gallery of images based on a natural language description. It presents a significant challenge due to the complexity of real-world scenes and the am…

Cross-Modal Retrieval Person Retrieval Re-Ranking Retrieval+2

Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings

2018-05-12 · Seonwook Park, Xucong Zhang, Andreas Bulling, Otmar Hilliges

Conventional feature-based and model-based gaze estimation methods have proven to perform well in settings with controlled illumination and specialized cameras. In unconstrained real-world settings, however, such methods…

Gaze Estimation

ShARc: Shape and Appearance Recognition for Person Identification In-the-wild

2023-10-24 · Haidong Zhu, Wanrong Zheng, Zhaoheng Zheng, Ram Nevatia

Identifying individuals in unconstrained video settings is a valuable yet challenging task in biometric analysis due to variations in appearances, environments, degradations, and occlusions. In this paper, we present ShA…

Person Identification

Interactive Natural Language-based Person Search

2020-02-19 · Vikram Shree, Wei-Lun Chao, Mark Campbell

In this work, we consider the problem of searching people in an unconstrained environment, with natural language descriptions. Specifically, we study how to systematically design an algorithm to effectively acquire descr…

Person Search Question Answering

Eye Gaze Estimation Model Analysis

2022-07-28 · Aveena Kottwani, Ayush Kumar

We explore techniques for eye gaze estimation using machine learning. Eye gaze estimation is a common problem for various behavior analysis and human-computer interfaces. The purpose of this work is to discuss various mo…

Gaze Estimation model