Peripheral Camera Image Classification for Vehicle BYOD Feeds

The patent segments the image analysis process into multiple stages: initial frame classification (keyframe/delta frame), frame size comparison, pixel value difference analysis, and motion vector examination. This segmentation allows the system to process images through a series of simpler, less computationally intensive steps rather than applying one complex algorithm, thereby maintaining classification accuracy while reducing overall computational complexity.

The patent implements partial action by applying multiple analysis techniques but only executing the full suite of algorithms when necessary. The system first applies lighter computational methods (frame classification, size comparison, pixel difference) and only proceeds to more intensive motion vector analysis when preliminary checks indicate potential exterior environment data, thus achieving accurate classification while avoiding unnecessary computational overhead.

The patent applies preliminary action by performing initial frame classification and basic comparisons before executing more time-consuming verification algorithms. The system first categorizes frames as keyframes or delta frames and performs quick pixel value difference checks, which filter out many interior environment captures before requiring intensive processing, thus maintaining data accuracy while significantly reducing average processing time.

The patent implements periodic action through its multi-stage analysis approach, where different levels of computational intensity are applied at different stages. The system periodically checks frame properties using increasingly sophisticated methods only when previous stages indicate potential exterior environment data, creating a rhythm of light and heavy processing that maintains accuracy while optimizing processing time.

The patent segments the classification process into multiple independent stages, each with its own computational characteristics. The first stage uses simple frame classification and size comparison for rapid processing, while subsequent stages apply more sophisticated analysis only when needed. This segmentation allows the system to achieve high processing speed for the majority of cases while maintaining accuracy through selective application of more complex methods.

The patent applies partial action by using simple classification methods for the initial processing of all frames, then selectively applying more accurate but computationally intensive verification only when preliminary results suggest potential exterior environment data. This approach ensures high processing speed for routine cases while maintaining classification accuracy for ambiguous or critical cases.