Intelligent video surveillance system and method

A system for training an object detection device, comprising:

• a recording device for recording a first video stream from a security camera;
• a processor operatively connected to said recording device, said processor programmed to select a set of frames from the first video stream;
• said processor further programmed to select a subset of frames from the set of frames and inserting a bounding box in each frame of the subset of frames;
• said processor further programmed to create a list of attributes associated with said each frame of the subset of frames;
• a database operatively connected to said processor, wherein said processor populates said database such that said database comprises said each frame of the subset of frames and the associated list of attributes, wherein said database is searchable by at least one attribute of the list of attributes;
• said processor further programmed to train a detection model using the database, wherein the training includes varying a first parameter of the detection model;
• said processor further programmed to analyze a second video stream using the detection model to determine a number of true positive events and a number of false positive events, wherein the second video stream is different from the first video stream;
• said processor further programmed to create a dataset of the analysis of the second video stream;
• said processor further programmed to filter the dataset using a second parameter;
• said processor further programmed to evaluate a performance of the detection model, at least in part, by:
• determining a ratio of true positive events to false positive events (“TP/FP”),
• determining a ratio of false positive events to true positive events (“FP/TP”),
• converting the FP/TP to a percentage (“% FP/TP), and
• determining a ratio of % FP/TP to TP/FP.

A non-transitory, machine-readable medium having stored thereon a plurality of

• executable instructions, the plurality of executable instructions comprising instructions to:
• record a first video stream from a security camera;
• select a set of frames from the first video stream;
• select a subset of frames from the set of frames and inserting a bounding box in each frame of the subset of frames;
• create a list of attributes associated with said each frame of the subset of frames;
• create a database comprising said each frame of the subset of frames and the associated list of attributes, wherein the database is searchable by at least one attribute of the list of attributes;
• train a detection model using the database, wherein the training includes varying a first parameter of the detection model;
• analyze a second video stream using the detection model to determine a number of true positive events and a number of false positive events, wherein the second video stream is different from the first video stream;
• create a dataset of the analysis of the second video stream;
• filter the dataset using a second parameter
• determine a ratio of true positive events to false positive events (“TP/FP”);
• determine a ratio of false positive events to true positive events (“FP/TP”);
• convert the FP/TP to a percentage (“% FP/TP);
• and
• evaluate a performance of the detection model based at least in part on a ratio of % FP/TP to TP/FP.