Pixel-wise exposure improves heart rate detection in cars
Pixel-wise Exposure for Highly Robust In-Vehicle Remote-PPG
Computer Vision and Pattern Recognition
Summary
Heart rate monitors that use cameras can struggle in cars because sunlight makes parts of the face too bright or too dark. The authors created a new method called PixExpo that changes the camera exposure for each pixel instead of the whole image at once. This method picks the best exposure for each pixel to capture clearer signals for heart rate without changing the camera hardware. Tests with real drivers showed it is much better than usual camera settings at tracking heart rate accurately.
What this means in practice
- •For automotive system developers: Build driver monitoring systems that measure heart rate accurately even in challenging cabin lighting conditions by using pixel-wise exposure control.$Commercial implications: Enables sale of advanced in-vehicle health monitoring systems improving safety and comfort under varying light conditions.
- •For wearable device engineers: Improve non-contact heart rate sensors for devices used in environments with complex lighting by integrating pixel-wise exposure techniques.
Authors
Jieying Wang, Xinqi Cai, Caifeng Shan, Wenjin Wang
Abstract
Remote photoplethysmography (rPPG) offers a promising non-contact solution for heart rate monitoring, yet its real-world robustness is fundamentally limited by an inherent hardware limitation: existing camera exposure control paradigms, whether fixed or auto-exposure, impose a uniform exposure time across all pixels within a frame. In high-dynamic-range scenes such as automotive cabins with strong directional sunlight, this spatially invariant exposure constraint inevitably leads to localized facial overexposure or underexposure, irreversibly corrupting the subtle pulsatile signals essential for rPPG at the point of capture, a physical degradation that no downstream algorithm can recover. To overcome this bottleneck, we propose PixExpo (Pixel-wise Exposure), a "temporal-for-spatial" framework that sequentially captures frames under a predefined cyclic exposure schedule and performs non-iterative pixel-wise fusion. At each pixel location, PixExpo selects the observation closest to an rPPG-motivated target intensity. This criterion seeks to reduce local saturation and severe underexposure rather than optimize perceptual appearance. PixExpo requires no sensor modification but assumes programmable frame-level exposure control. We validate the proposed PixExpo framework using our newly introduced MEX-Drive dataset, comprising 48 participants under real-world driving conditions. Experimental results demonstrate that PixExpo outperforms manufacture-default auto-exposure methods, reducing the mean absolute error (MAE) by 7.21 bpm (from 13.94 to 6.73 bpm) and increasing the success rate by 37.29 percentage points (from 25.95% to 63.24%) across challenging driving scenarios.