Rank Persistence: Assessing the Temporal Performance of Real-World Person Re-Identification
Designing useful person re-identification systems for real-world applications requires attention to operational aspects not typically considered in academic research. Here, we focus on the temporal aspect of re-identification; that is, instead of finding a match to a probe person of interest in a fixed candidate gallery, we consider the more realistic scenario in which the gallery is continuously populated by new candidates over a long time period. A key question of interest for an operator of such a system is: how long is a correct match to a probe likely to remain in a rank-k shortlist of possible candidates? We propose to distill this information into a Rank Persistence Curve (RPC), which allows different algorithms' temporal performance characteristics to be directly compared. We present examples to illustrate the RPC using a new long-term dataset with multiple candidate reappearances, and discuss considerations for future re-identification research that explicitly involves temporal aspects.
Code (0)
등록된 구현이 없습니다.
Tasks
Person Re-IdentificationSimilar Papers 제목 키워드 기반
Method to Assess the Temporal Persistence of Potential Biometric Features: Application to Oculomotor, and Gait-Related Databases
Although temporal persistence, or permanence, is a well understood requirement for optimal biometric features, there is no general agreement on how to assess temporal persistence. We suggest that the best way to assess t…
Building for Tomorrow: Assessing the Temporal Persistence of Text Classifiers
Performance of text classification models tends to drop over time due to changes in data, which limits the lifetime of a pretrained model. Therefore an ability to predict a model's ability to persist over time can help d…
Classificationtext-classificationText ClassificationEvaluating Temporal Persistence Using Replicability Measures
In real-world Information Retrieval (IR) experiments, the Evaluation Environment (EE) is exposed to constant change. Documents are added, removed, or updated, and the information need and the search behavior of users is …
Information RetrievalRetrievalAnalyzing the Effectiveness of Listwise Reranking with Positional Invariance on Temporal Generalizability
This working note outlines our participation in the retrieval task at CLEF 2024. We highlight the considerable gap between studying retrieval performance on static knowledge documents and understanding performance in rea…
BenchmarkingDecoderInformation RetrievalReranking+1Conditional Rank-Rank Regression
Rank-rank regression is commonly employed in economic research as a way of capturing the relationship between two economic variables. It frequently features in studies of intergenerational mobility as the resulting coeff…
regression