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# Best Meeting Point

A group of two or more people wants to meet and minimize the total travel distance. You are given a 2D grid of values `0` or `1`, where each `1` marks the home of someone in the group. The distance is calculated using [Manhattan Distance](https://en.wikipedia.org/wiki/Taxicab_geometry), where `distance(p1, p2) = |p2.x - p1.x| + |p2.y - p1.y|`.

#### Example

**Example 1:**

```
Input:
[[1,0,0,0,1],[0,0,0,0,0],[0,0,1,0,0]]
Output:
6

Explanation:
The point `(0,2)` is an ideal meeting point, as the total travel distance of `2 + 2 + 2 = 6` is minimal. So return `6`.
```

**Example 2:**

```
Input:
[[1,1,0,0,1],[1,0,1,0,0],[0,0,1,0,1]]
Output:
14
```

```java
// BFS approach will TLE
public class Solution {
    public int minTotalDistance(int[][] grid) {
        ArrayList<Integer> row = new ArrayList<>();
        ArrayList<Integer> col = new ArrayList<>();
        for (int i = 0; i < grid.length; i++)
            for (int j = 0; j < grid[0].length; j++)
                if (grid[i][j] == 1) {
                    row.add(i);
                    col.add(j);
                }
        Collections.sort(row);
        Collections.sort(col);
        int size = row.size();
        // Min sum distance point is always median
        int x = row.get(size / 2);
        int y = col.get(size / 2);
        int dist = 0;
        for (int i = 0; i < grid.length; i++)
            for (int j = 0; j < grid[0].length; j++)
                if (grid[i][j] == 1)
                    dist += Math.abs(x - i) + Math.abs(y - j);
        return dist;
    }
}
```


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