Method and system for splitting visual sensor data

A non-transitory computer-readable medium having processor-executable instructions stored thereon for automatically splitting visual sensor data comprising consecutive images, wherein the processor-executable instructions, when executed by at least one processor of a host computer, facilitate:

• a) assigning a scene number to each image, wherein a scene comprises a plurality of images taken in a single environment, wherein assigning a scene number to each image is performed based on a comparison between consecutive images, the comparison being based on one or more of:
• optical flow;
• Global Positioning System (GPS) coordinates;
• Inertial Measurement Unit (IMU) acceleration data;
• or
• file properties;
• b) determining an accumulated effort for the images in each scene, wherein the accumulated effort is determined based on the number of objects in the images of the scene, wherein the number of objects is determined using one or more neural networks for object detection;
• and
• c) creating packages of images, wherein the images with the same scene number are assigned to the same package unless the accumulated effort of the images in the package surpasses a package threshold.

A computer system, comprising a processor and a non-transitory computer-readable medium having processor-executable instructions stored thereon for automatically splitting visual sensor data comprising consecutive images, wherein the processor-executable instructions, when executed by the processor, facilitate the following operations being performed by the computer system:

• a) assigning a scene number to each image, wherein a scene comprises a plurality of images taken in a single environment, wherein assigning a scene number to each image is performed based on a comparison between consecutive images, the comparison being based on one or more of:
• optical flow;
• Global Positioning System (GPS) coordinates;
• Inertial Measurement Unit (IMU) acceleration data;
• or
• file properties;
• b) determining an accumulated effort for the images in each scene, wherein the accumulated effort is determined based on the number of objects in the images of the scene, wherein the number of objects is determined using one or more neural networks for object detection;
• and
• c) creating packages of images, wherein the images with the same scene number are assigned to the same package unless the accumulated effort of the images in the package surpasses a package threshold.