Distance between cursor Task $2-$ Understand and Implement the Algorithm of Target Selection with the

Bubble Cursor

The algorithm proposed in $[1]$ is used to continuously update the radius of the bubble cursor, such

that there is always exactly one target within its activation area. To describe the algorithm in an

environment with objects $T_1,T_2,$dots,$T_n,$ we adopt the following definitions as $[1]$:

Intersecting Distance i $($ IntD $D_i)$: The length of the shortest line connecting the centre of the bubble

cursor and any point on the border of $T_i.lnt{D}_i$ can be calculated as the distance between the cursor

and ob

Figure $3.$ How to calculate ConD. The black cross indicates the cursor centre. The green circle is an

object.

A simplified version of the algorithm is below:

Set $i=$ index of closest target $(T_i)$ by intersecting distance

Set $j=$ index of second closest target $(T_j)$ by intersecting distance

Set radius of bubble cursor $=$min$(Con{D}_i,lnt{D}_j)$

This algorithm ensures that the bubble cursor will at least intersect the closest object, and possibly

completely contain it$.$ When the bubble only intersects the closest object and does not completely

contain it$,$ we morph the cursor by extending a second bubble which quickly expands from the

intersection points and envelopes the object $($Fig$\mathrm{.}1$b$).$ This acts as a reinforcing visual cue to the

user that the object is indeed captured by the cursor.

Hints: you need to implement the algorithm in the function in area$\_$cursor.py: def

determine selected object$($self$,x,y)$: