Systems and methods for mitigating false negatives in neural network-based object detection

A computer vision object detection system, the system comprising:

• a processor including a Neural Network based object detector (NN-detector) module and a light informed shape analysis (LISA) module, wherein the processor is configured to:
• receive an image scene;
• cause the NN-detector module to:
• scan the image scene to identify an object as an object of interest;
• identify a region of interest for the object of interest;
• generate a bounding box that encompasses the object of interest and the region of interest;
• and
• track position or movement of the object of interest;
• when the NN-detector drops the bounding box for the object of interest, cause the LISA module to:
• extract a region of interest for use as an expected region of interest for the object of interest;
• extract one or more shape contours of the object of interest for use as a representation of the object of interest;
• and
• track position or movement of the object of interest.