1. An automatic vision sensor placement method comprising: modeling a specified space as a 2D grid map; expressing the space priority of each cell of the grid map in a numerical value based on an amount of movement of an agent in a first area of the grid map and a probability that the agent will move from the first area to a second area; extracting the suitability of a vision sensor at each location on the grid map based on a sum of space priority values of cells within a field of view (FOV) of the vision sensor and a performance and cost of the vision sensor; and calculating a number of vision sensors to be placed based on a maximum vision sensor placement cost and minimum space coverage and selecting locations, at which the vision sensor is to be placed, in order of highest to lowest suitability of the vision sensor, wherein the FOV of the vision sensor is defined by a viewing distance d, available angle a, and position angle Φ of the vision sensor at a specified coordinate point, and the minimum space coverage is the proportion of a minimum area that can be monitored by the vision sensor in the specified space, wherein the modeling of the specified space comprises: creating a wall or space layer that separate a walkable space from a non-walkable space in the specified space; creating an area layer which contains information about an amount of movement of a user in the first area of the 2D grid map, a probability that the user will move from the first area to the second area, and a center coordinate and a radius of each of the first area and the second area; and creating a priority layer which represents extracted space priority values of the cells on the grid map, wherein the movement of the agent from the first area to the second area is modeled using an A* search algorithm which is based on a shortest and least-cost path and a path expansion algorithm, and wherein the path expansion algorithm comprises: identifying a range r 1 of an area around a specified starting point and a range r 2 of an area around a specified destination based on the area attribute information; calculating a number n of starting points within the range r 1 of the area around the specified starting point and determining the positions of the n starting points; calculating a number m of destinations within the range r 2 of the area around the specified destination and determining the positions of the m destinations; finding (n+1)×(m+1) additional paths by applying the A* algorithm to the (n+1) starting points including the specified starting point and to the (m+1) destinations including the specified destination; finding grid cells surrounded by lines of the additional paths and add the found grid cells as additional areas; returning grid cells for all additional paths and the grid cells as additional areas; and adjusting a space priority value included in the searched path.