ADAPTIVE EMOTION-BASED CAMERA ISP TUNING

Smart overview of the Invention

A novel system integrates adaptive emotion-based image signal processor (ISP) parameter tuning, leveraging advanced neural networks to enhance image quality based on emotional context. This approach involves detecting subtle facial micro-expressions and analyzing conversational cues to dynamically adjust ISP settings, ensuring the captured image reflects the scene's mood accurately.

Neural Network Integration

The system employs a neural network specifically designed to identify emotional cues within a scene. By focusing on facial micro-expressions, the network can interpret nuanced emotional states, which are then used to inform adjustments in ISP parameters. This capability allows for a more personalized and context-aware image processing experience.

Natural Language Processing

In addition to facial recognition, the system utilizes natural language processing (NLP) to extract mood indicators from conversations. By transcribing and analyzing spoken words within a scene, the NLP model provides further emotional context, contributing to more precise ISP tuning based on the overall mood conveyed verbally.

Dynamic ISP Parameter Adjustment

The system dynamically adjusts various ISP parameters, such as those within tone mapping, color correction matrix, and sharpening blocks. These adjustments are made in real-time and are directly influenced by the detected emotional cues, ensuring that the final image output aligns with the intended emotional tone of the scene.

Software Component Integration

Designed as a software component, this adaptive emotion-based tuning can be seamlessly integrated into existing camera systems. The flexibility of software implementation ensures broad compatibility and allows for updates and improvements without requiring hardware changes, making it a versatile solution for enhancing image processing through emotional context awareness.