# Advanced Acceptance Score: A Holistic Measure for Biometric Quantification

arXiv: https://arxiv.org/abs/2602.15535 · HTML: https://mlsanity.com/paper/2602.15535/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 21 of its 47 references that are in the map.
- First posted on arXiv 17 Feb 2026.

## Builds on (most cited first, 21 of 21)

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- [TAM: Temporal Adaptive Module for Video Recognition](https://mlsanity.com/paper/2005.06803/) (2020)
- [Fairness in Biometrics: a figure of merit to assess biometric verification systems](https://mlsanity.com/paper/2011.02395/) (2020)
- [What is the Best Automated Metric for Text to Motion Generation?](https://mlsanity.com/paper/2309.10248/) (2023)
- [On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top-n Recommendation](https://mlsanity.com/paper/2307.15053/) (2023)
- [TinyRadarNN: Combining Spatial and Temporal Convolutional Neural Networks for Embedded Gesture Recognition with Short Range Radars](https://mlsanity.com/paper/2006.16281/) (2020)
- [On the (Limited) Generalization of MasterFace Attacks and Its Relation to the Capacity of Face Representations](https://mlsanity.com/paper/2203.12387/) (2022)
- [GestFormer: Multiscale Wavelet Pooling Transformer Network for Dynamic Hand Gesture Recognition](https://mlsanity.com/paper/2405.11180/) (2024)
- [Evaluation Measures for Relevance and Credibility in Ranked Lists](https://mlsanity.com/paper/1708.07157/) (2017)
- [An Axiomatic Analysis of Diversity Evaluation Metrics: Introducing the Rank-Biased Utility Metric](https://mlsanity.com/paper/1805.02334/) (2018)
- [On the Biometric Capacity of Generative Face Models](https://mlsanity.com/paper/2308.02065/) (2023)
- [Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance](https://mlsanity.com/paper/2405.18276/) (2024)
- [Principled Multi-Aspect Evaluation Measures of Rankings](https://mlsanity.com/paper/2212.00492/) (2022)
- [Findability: A Novel Measure of Information Accessibility](https://mlsanity.com/paper/2310.09508/) (2023)
- [Revisiting Human Action Recognition: Personalization vs. Generalization](https://mlsanity.com/paper/1605.00392/) (2016)
- [Offline Retrieval Evaluation Without Evaluation Metrics](https://mlsanity.com/paper/2204.11400/) (2022)
- [Fairness measures for biometric quality assessment](https://mlsanity.com/paper/2408.11392/) (2024)

## Abstract (arXiv)

Quantifying biometric characteristics within hand gestures involve derivation of fitness scores from a gesture and identity aware feature space. However, evaluating the quality of these scores remains an open question. Existing biometric capacity estimation literature relies upon error rates. But these rates do not indicate goodness of scores. Thus, in this manuscript we present an exhaustive set of evaluation measures. We firstly identify ranking order and relevance of output scores as the primary basis for evaluation. In particular, we consider both rank deviation as well as rewards for: (i) higher scores of high ranked gestures and (ii) lower scores of low ranked gestures. We also compensate for correspondence between trends of output and ground truth scores. Finally, we account for disentanglement between identity features of gestures as a discounting factor. Integrating these elements with adequate weighting, we formulate advanced acceptance score as a holistic evaluation measure. To assess effectivity of the proposed we perform in-depth experimentation over three datasets with five state-of-the-art (SOTA) models. Results show that the optimal score selected with our measure is more appropriate than existing other measures. Also, our proposed measure depicts correlation with existing measures. This further validates its reliability. We have made our hrefhttps://github.com/AmanVerma2307/MeasureSuitecode public.