A Novel Approach for Privacy Preserving Object Re-Identification on Edge Devices

Abstract

Computer vision approaches have been widely used in mobility tasks such as visitor counting, traffic analyisis, etc. The European General Data Protection Regulation (GDPR) enforces in-camera processing as storing and transmitting such data violates this regulation. This paper introduces a novel approach for object Re-Identification (Re-ID) on edge devices using a color based encoded virtual plane for location mapping. The method leverages the spatial coding capabilities of the RGB color space to simplify the localisation process. By assigning unique RGB values to spatial coordinates, creating a multidimensional reference image that facilitates instant and accurate object localisation. This reduces computational complexity and allows global referencing across multiple cameras. We present an algorithmic framework for location mapping and demonstrating its capability through experimental validation. The techniques potential is further explored in applications such as object Re-ID, marking a significant advancement in computer vision and expanding the branch of spatial encoding methodologies. This approach represents a shift towards more privacy-oriented multi camera object tracking and Re-ID solutions.

Keywords

• data privacy
• object location
• spatial encoding
• object tracking
• object re-identification