Multi-Sensor Object Recognition System and Method

A computing device for detecting objects, the computing device comprising:

• a memory;
• an imaging controller comprising:
• an image preprocessor configured to obtain a set of images from the memory depicting overlapping regions of an area containing a plurality of objects, each of the set of images including a plurality of input object indicators;
• a subset detector configured to identify candidate subsets of input object indicators in adjacent ones of the set of images, each candidate subset having input bounding boxes that overlap in a common frame of reference, and a common object identifier;
• the subset detector further configured to adjust input confidence level values upwards from initial values for each input object indicator in the candidate subsets;
• a cluster detector configured to select clusters of the input object indicators, the input object indicators of each cluster satisfying a minimum input confidence threshold, having a common object identifier, and having a degree of overlap that satisfies a predefined threshold;
• and
• an output generator configured to detect an object by generating a single output object indicator for each cluster.

A non-transitory computer readable storage medium containing a plurality of computer readable instructions executable by an imaging controller to configure the imaging controller to perform a method of object detection comprising:

• obtaining a set of images depicting overlapping regions of an area containing a plurality of objects, each of the set of images including a plurality of input object indicators;
• identifying candidate subsets of input object indicators in adjacent ones of the set of images, each candidate subset having input bounding boxes that overlap in a common frame of reference, and a common object identifier;
• adjusting input confidence level values upwards from initial values for each input object indicator in the candidate subsets;
• selecting clusters of the input object indicators, the input object indicators of each cluster satisfying a minimum input confidence threshold, having a common object identifier, and having a degree of overlap that satisfies a predefined threshold;
• and
• detecting an object by generating a single output object indicator for each cluster.