Multi-Step Object Re-Identification on Edge Devices: A Pipeline for Vehicle Re-Identification

A presentation about article: "Multi-Step Object Re-Identification on Edge Devices: A Pipeline for Vehicle Re-Identification" that was submitted and presented in EEAI2024 conference. A method that leverages a multi-step process focused on extracting and using object features for object re-identification is described. The proposed pipeline includes steps such as: detecting an object, converting its features into a vector embedding, storing this embedding in a vector database, and then querying the database to find the same or similar objects based on their feature embeddings. This approach allows for the identification of the same object across different images or cameras, even in varying locations, such as in Vehicle Re-Identification scenarios. For a process like Vehicle Re-identification implementing this process on edge devices becomes crucial. Therefore, ways to tailor the pipeline and its outputs for edge devices are outlined. The paper provides a detailed explanation of the pipeline’s structure along with the experimental setup demonstrating its application, particularly in vehicle re-identification. The pipeline achieves 70-80% re-identification precision when dealing with vehicle images from our network cameras and above 70% Rank-1 accuracy when dealing with a CityFlow video track scenario.