# Cost-based Feature Transfer for Vehicle Occupant Classification

arXiv: https://arxiv.org/abs/1512.07080 · HTML: https://mlsanity.com/paper/1512.07080/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Dec 2015.

## Built on by (most cited first, 2 of 2)

- [TICaM: A Time-of-flight In-car Cabin Monitoring Dataset](https://mlsanity.com/paper/2103.11719/) (2021)
- [Autoencoder Based Inter-Vehicle Generalization for In-Cabin Occupant Classification](https://mlsanity.com/paper/2105.03164/) (2021)

## Abstract (arXiv)

Knowledge of human presence and interaction in a vehicle is of growing interest to vehicle manufacturers for design and safety purposes. We present a framework to perform the tasks of occupant detection and occupant classification for automatic child locks and airbag suppression. It operates for all passenger seats, using a single overhead camera. A transfer learning technique is introduced to make full use of training data from all seats whilst still maintaining some control over the bias, necessary for a system designed to penalize certain misclassifications more than others. An evaluation is performed on a challenging dataset with both weighted and unweighted classifiers, demonstrating the effectiveness of the transfer process.