In recent years, there has been an increasing interest in image anonymization, particularly focusing on the de-identification of faces and individuals. However, for self-driving applications, merely de-identifying faces and individuals might not provide sufficient privacy protection since street views like vehicles and buildings can still disclose locations, trajectories, and other sensitive information. Therefore, it remains crucial to extend anonymization techniques to street view images to fully preserve the privacy of users, pedestrians, and vehicles. In this paper, we propose a Street View Image Anonymization (SVIA) framework for self-driving applications. The SVIA framework consists of three integral components: a semantic segmenter to segment an input image into functional regions, an inpainter to generate alternatives to privacy-sensitive regions, and a harmonizer to seamlessly stitch modified regions to guarantee visual coherence. Compared to existing methods, SVIA achieves a much better trade-off between image generation quality and privacy protection, as evidenced by experimental results for five common metrics on two widely used public datasets.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    SVIA: A Street View Image Anonymization Framework for Self-Driving Applications


    Contributors:
    Liu, Dongyu (author) / Wang, Xuhong (author) / Chen, Cen (author) / Wang, Yanhao (author) / Yao, Shengyue (author) / Lin, Yilun (author)


    Publication date :

    2024-09-24


    Size :

    10502310 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    IMAGE ANONYMIZATION APPARATUS, IMAGE ANONYMIZATION METHOD, AND PROGRAM

    AIZAWA CHITEI | European Patent Office | 2021

    Free access

    ANONYMIZATION SYSTEM

    KOMATSU SHUHEI | European Patent Office | 2019

    Free access

    POSITION INFORMATION ANONYMIZATION METHOD, MOVEMENT INFORMATION ANONYMIZATION METHOD, AND DEVICE

    HIKITA TOSHIRO / YANAGIHARA TADASHI / TANAKA YUSUKE et al. | European Patent Office | 2016

    Free access

    VIEW SYNTHESIS FOR SELF-DRIVING

    ZHUANG BINGBING / JIANG ZIYU / LIU BUYU et al. | European Patent Office | 2025

    Free access

    SYSTEM AND METHOD FOR VEHICLE LOCATION ANONYMIZATION

    TINSLEY BRYAN PATRICK / HATFIELD CAMERON CARSON / GARLICK MICHAEL SHAWN | European Patent Office | 2022

    Free access