## 3 Experiment
### Evaluating Indicator
#### 3.4.2 Objective Scoring  
For the objective evaluation of layout quality, it is primarily based on aesthetic principles and layout-related criteria. This paper employs an energy-based model \(E(X;\theta)\), using parameter \(\theta\) to assess the layout \(X\) of the presentation. The overall quality of the layout is measured by the weighted sum of energy terms:  
\[E(X;\theta)=\sum_{i}\omega_{i}E_{i}(X;\alpha_{i}). \tag{13}\]  
In this context, the design layout \(X\) is defined for each object's position, metadata, width, and height, with _theta_ representing the model parameters. The model parameters are divided into two groups, \(\theta\ =\ [\omega;\ a]\). Each energy term \(E_{i}\) has positive weights \(omega_{i}\), and most terms involve non-linear parameters \(alpha_{i}\). The energy function incorporates various design principles, including alignment, balance, white space, scale, overlap, and boundaries. The definitions of each energy term are provided below. 1. Alignment Alignment is crucial for design, especially in limited space where efficient information transmission and aesthetically pleasing organization are prioritized. The first consideration in this context is the alignment of various elements. This paper defines six possible alignment types: Left, X-center, Right, Top, Y-center, and Bottom. Before defining the alignment energy term, an analysis phase is executed, marking all aligned objects and alignment groups. A simple heuristic algorithm is employed to compute the alignment of object bounding boxes. Initially, the difference between the edges or center positions of the bounding boxes must be smaller than a threshold: \[A_{ij}^{a}=\left(d_{ij}^{a}<\tau_{align}\right),\] (14) where a is the alignment type and \(d_{ij}^{a}\) represents the distance between two objects i and j, depending on the alignment type used for the bounding boxes of the objects. For example, if a = Left, then \(d_{ij}\) Left measures the difference between the left edges of the bounding boxes of two objects. The threshold is set to \(\tau_{align}\)=0.065, allowing slightly misaligned objects to still be marked as aligned. Secondly, if an object is positioned between other objects, the objects may not align: \[B_{ij}=\left(b_{ij}<1\right),\] (15) where \(b_{ij}\) is the number of objects between i and j. Next, the alignment indicator is defined. The alignment indicator variable between objects i and j, denoted as \(I_{ij}^{a}\), is a combination of the terms mentioned above: \[I_{ij}^{a}=A_{ij}^{a}\wedge B_{ij}\wedge N_{i}^{a}\wedge N_{j}^{a}.\] (16) In each axis, two objects typically align with only a single type. The minimum alignment distance \(d_{ij}^{a}\) is set to 1, while the other two are set to 0. However, if all types are perfectly aligned (\(d_{ij}^{a}\)= 0 for all types), then all three indicators are set to 1. Next, the aligned group is defined as a set of connected aligned objects. If objects \(i\) and \(k\) are aligned and objects \(k\) and \(j\) are aligned with the same type, then \(i\) and \(j\) are set to be aligned, i.e., \(I_{ij}^{a}=I_{ijk}^{a}\wedge I_{kj}^{a}\). Finally, the alignment energy term is defined, measuring the proportion of objects aligned with a specific alignment type. Larger alignment groups are encouraged, asthey result in simpler designs and greater uniformity between objects. The alignment energy term measures the score of pairs of objects aligned with type \(a\):  
\[E_{align}^{a}=S\left(\left|\frac{1}{n^{2}}\sum_{i\in(all)}\left(N_{i}^{a}+\sum_ {j\in(all)}I_{ij}^{a}\right)-1\right|;\alpha_{a}\right), \tag{17}\]  
where \(n\) is the number of objects and \(I_{ij}^{a}\) indicates whether objects \(i\) and \(j\) are aligned according to type \(a\). Different alignment types define separate energy terms. \(N_{i}^{a}\) indicates whether \(i\) is a text object aligned internally within type \(a\). Each feature is transformed by \(S(x;\alpha)\), which is a smooth step function defined by the following formula.