Video monitoring method, video monitoring system and computer program product

A video monitoring system comprising:

• a processor;
• a memory;
• and
• computer program instructions stored in the memory, which, when executed by the processor, perform the steps of:
• obtaining video data collected by a video collecting apparatus;
• determining an object as a monitoring target based on the video data;
• and
• extracting feature information of the object,
• wherein the video data is video data containing depth information, and
• wherein the step of determining the object as the monitoring target based on the video data performed by the computer program instructions when executed by the processor comprises:
• determining background information in the video data;
• determining foreground information in each frame of the video data based on the background information;
• obtaining edge profile information of a foreground area corresponding to the foreground information;
• obtaining a candidate block based on the edge profile information;
• determining the candidate block larger than a first predetermined threshold as a candidate object;
• obtaining an evaluation value of the candidate object based on a predetermined algorithm;
• and
• determining the candidate object whose evaluation value is larger than a second predetermined threshold as the object.

A non-transitory computer program product comprising a computer readable storage medium on which computer program instructions are stored, wherein the computer program instructions, when executed by the processor, perform the steps of:

• obtaining video data collected by a video collecting apparatus;
• determining an object as a monitoring target based on the video data;
• and
• extracting feature information of the object,
• wherein the video data is video data containing depth information, and
• wherein the step of determining the object as the monitoring target based on the video data performed by the computer program instructions when executed by the processor comprises:
• determining background information in the video data;
• determining foreground information in each frame of the video data based on the background information;
• obtaining edge profile information of a foreground area corresponding to the foreground information;
• obtaining a candidate block based on the edge profile information;
• determining the candidate block larger than a first predetermined threshold as a candidate object;
• obtaining an evaluation value of the candidate object based on a predetermined algorithm;
• and
• determining the candidate object whose evaluation value is larger than a second predetermined threshold as the object.