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Uniform Path Cost Search-Artificial intelligence
A breadth first search will search the solution with the shortest path length from the first state to the goal state. Though, this cannot be the least costly solution in terms of the path cost. A uniform path cost search selects which node to expand by looking at the path cost for every node: the node which has cost least to get to is expanded firstly. Therefore, if, as is usually the case, the path cost of a node increases with the path length, then this search is guaranteed to search the least expensive solution. It is therefore an optimal search strategy. Unluckily, this search strategy may not be very efficient.
I am using block matching algorithm to get the motion vectors, now, how can I get the depth map/depth value from the motion vectors?
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