The overall process for recognizing human actions in aerial videos is depicted in Figure 2. The proposed system follows a specific workflow: it begins with an input video, which is then processed to extract individual frames. These frames are then passed through the human detection module. The human detection module utilizes a scaled YOLOv4[28] algorithm to identify individuals within the extracted frames. The resulting low-resolution (LR) detections are then inputted into the image enhancement module, which transforms them into high-resolution (HR) images. These high-resolution images are subsequently fed into the human action recognition module for further analysis. In the following section, we will delve into each of these components in greater detail.
3.1 Image Enhancement module
The image enhancement module shown in Figure 3, generates high resolution images corresponding to each low-resolution image i.e. the detected humans. The image enhancement module’s training process involves two neural networks, namely the generator (G) and the discriminator (D), updated simultaneously until a Nash equilibrium is reached. The generator's objective is to produce synthetic data that is indistinguishable from real data, while the discriminator's objective is to classify the data as real or fake accurately. The generator includes residual in residual dense blocks (RRDB), similar to the ESRGAN[26] generator. A relativistic discriminator, similar to the ESRGAN architecture, is used to differentiate between high-resolution and super-resolved images generated by the generator. The discriminator takes in the generated super resolution image (SR). Notably, the discriminator in this model differs from the conventional CNN network as it employs an MLP-mixer network[29]. The use of an MLP-mixer network presents several benefits, such as relying solely on multilayer perceptrons without convolution or attention mechanisms. Additionally, it involves basic matrix multiplication routines that are less computationally demanding than convolution operations. By utilizing the MLP Mixer architecture, it is possible to decrease the number of parameters required and reduce the overall computation time while still achieving comparable performance to solutions based on convolutional neural networks (CNNs).
The MLP-Mixer network comprises MLP blocks and a Mixer layer, which are fundamental formulations in the model. The input SR image is first transformed into patches, and then the MLP-Mixer network takes these patches, which are linearly distributed, and converts them into vectors with the help of fully connected layer applied to each patch. Each patch is projected to a desired hidden dimension, resulting in a two-dimensional input table, denoted as X with dimensions PxC, where P represents the patches and C represents the dimension/channels. These vectors are then passed to the Mixer layer. To calculate the total number of patches, S, we divide the total number of pixels in the original input image, H x W, by patch size. Therefore,
![](data:image/png;base64,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)
In our case, we have the SR image size as 150x150 and a patch size of 15x15. The Mixer layer includes two types of blocks, namely, the patch-mixing block and channel-mixing block. The patch-mixing block enables interaction between different spatial locations, while the channel-mixing block facilitates interaction between different channels. Both the blocks are supported by layer normalization and a skip-connection before and after each channel-mixing and patch-mixing block, respectively. The MLP modules present in both the blocks consist of two fully connected layers and the GELU activation function, are used in the model. The functioning of the Mixer layer can be expressed mathematically as follows:
![](data:image/png;base64,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)
In equation (1), X represents the matrix of patches, Y contains the intermediate features obtained from the patch mixer block. In equation (2), Z represents the final feature obtained from the channel mixer block and in equation (3), MLP denotes the multilayer perceptron module, which consists of fully connected layers and a GELU activation function. denotes the input received by the MLP module present in patch mixing and channel mixing blocks. The proposed image enhancement module comprises four mixer layers, and the output of the mixer layer is passed to a global average pooling layer followed by the last fully connected layer for classification. The loss functions and loss function parameters used are similar to those in ESRGAN. The generator uses perceptual loss, content loss, and adversarial loss.
![](data:image/png;base64,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)
3.2 Human Action Recognition Module
The proposed human action recognition module illustrated in Figure 4 is a modified ResNeXt101 model that incorporates squeeze and excitation networks[30]. The human action recognition module accepts the super resolved high resolution image, generated by the image enhancement module as input. The model comprises of a convolutional block followed by four SE-ResNeXt blocks, four fully connected layers, and a softmax layer for classification. The architecture of SE-ResNeXt block is depicted in Figure 5. The SE network is embedded in the ResNeXt block as an identical unit, similar to residual learning. The SE network serves as a channel attention mechanism, enabling the extraction of the most significant features from each channel of the feature map. The extracted information is then fused into the network with the aid of an identity mapping mechanism to facilitate the flow of this information through the network. Convolutional neural networks are highly dependent on convolution operations, which merge information from all channels. However, since each channel carries the same weight, the deep neural network lacks the ability to learn discriminately. Additionally, not all features contribute positively to feature extraction, so it is necessary for the network to focus on those features that are meaningful. The SE module addresses this issue by enabling the network to learn important features by establishing the correlation between channels and assigning weights to different channels. The SE mechanism's fundamental idea is to explicitly model channel-wise dependencies by capturing the interdependencies between feature channels. The SE mechanism comprises two crucial operations: squeezing and exciting.
The squeezing operation reduces the spatial dimensions of each feature map to a single value using a global average pooling operation, which produces a channel descriptor that reflects the significance of each channel in the feature map. Specifically, for a given feature map X with dimensions of HxWxC, where H represents the height, W represents the width, and C represents the number of channels, the squeeze operation generates a channel descriptor vector z of size (1,1,C). The excitation operation selectively amplifies the important channels using a learned weighting mechanism. Specifically, it learns a set of channel-wise weights that scale the channel descriptor obtained from the previous squeeze operation to produce a refined representation of the features. This refined representation highlights the informative channels and suppresses the less informative ones, resulting in a more discriminative feature map. To achieve this, the excitation operation employs a two-layer feedforward neural network. The first layer, called the reduction block, reduces the input space to a smaller space defined by a reduction factor, r. The second layer, called the expansion block, restores the compressed space back to the original dimensionality of the input tensor, resulting in a tensor of size (1,1,C). This excited tensor is then passed through a sigmoid activation function that scales the values to a range of 0-1, producing a refined representation that emphasizes the informative channels and suppresses the less informative ones. This output S is applied directly to the input tensor through a broadcasted element-wise multiplication operation ⊗. Each channel or feature map in the input tensor is scaled with its corresponding learned weight from the multi-layer perceptron in the excitation module.
Applying the SE network directly to the input features may lead to the loss of discriminative information. Therefore, to preserve the integrity of the original features, the SE network is added as an identity mapping. SE network improves the ability of a ResNeXt block to capture relevant and discriminative features by weighting and combining information contained in different channels of the input feature map. This fusion of features can provide a more informative and robust representation of the input, allowing the network to better distinguish between different classes or categories. By using the SE mechanism as an identity unit, the model can attend to the most informative channels in a feature map, reducing the impact of irrelevant features and improving the model's ability to distinguish between different categories or classes.