# Satellite Video Moving Vehicle Detection and Tracking Based on Spatiotemporal Characteristics
## 3 Methods
### Constraint Construction Based on the Spatiotemporal Domain  
Among the existing constraint construction methods, the motion-based accumulation method is unstable and requires the accumulation of a large number of video frames. Single-frame object-oriented classification methods for extracting road masks are prone to breakage and missing detections. The method for loading existing road maps has a high memory footprint and requires significant manual labeling. Therefore, DTSTC incorporates road masks and motion heat maps to improve the robustness of the constructed constraints. The road mask in this method fully utilizes spatial domain information and can provide an improved initial value for the motion heat map. The motion heat map uses time domain information, which complements the broken and missed detection parts of the road mask. In addition, this method has a small memory footprint compared to loading an existing road network and does not require extensive manual marking. The D-LinkNet road extraction fully considers the spatial representation characteristics of roads in a single image frame, including the narrowness, connectivity, complexity, and long spans. The network also exponentially increases the perceptual field of the model using a jump connection and null convolution module, making it more capable of road extraction. Then, ResNet34 [26] is used as the encoder to effectively solve the problem of losing image feature information during the convolution process. The network exhibited superior results in terms of road extraction when faced with satellite video data. Therefore, DTSTC used the D-LinkNet for road extraction from a single image frame to initialize the constraints. However, D-LinkNet only extracts the road mask using the spatial characteristics of a single frame of an image, does not take full advantage of the video data in the time domain, and cannot avoid the occurrence of broken and missing roads. Therefore, DTSTC complemented this by cumulatively generating a motion heat map using temporal differences. This temporal difference fully utilizes the target motion information between two successive frames and can effectively complement the road mask generated using only a single image frame. Figure 2 illustrates the general flow for generating a coarse-motion heat map using temporal differences. The video frames are first detected quickly using the temporal difference, which has a high detection efficiency. The results of each frame are then processed using mathematical morphology to remove the effects of random noise and pseudo-motion targets. Finally, the processing results were overlain to produce an approximate motion heat map. Figure 1: DTSTC flow diagram. The video frame data is processed in the order of left to right to obtain the tracking results. The input is the satellite video data, while the output is the tracking track result of the moving vehicle in image coordinates. The specific integration of the two is shown in Figure 3. The connected domain of the rough motion heat map was first preprocessed and filtered based on parameters such as the area (\(A\)), aspect ratio (\(A_{r}\)), perimeter-to-area ratio (\(R_{ca}\)), and surface roughness (\(S_{r}\)) to remove the influence of pseudo-motion targets. The aspect ratio and surface roughness were calculated using Equations (1) and (2), respectively:  
\[A_{r}=l\ /\ w, \tag{1}\]  
\[S_{r}=C_{mech}\ /\ C_{a}, \tag{2}\]  
where \(l\) denotes the minimum external rectangular length of the connected domain, and \(w\) denotes the minimum external rectangular width of the connected domain. \(C_{mech}\) is the minimum external convex envelope perimeter of the connected domain, and \(C_{a}\) is the connected domain perimeter. The preprocessed motion heat map was then graphically compared with the road mask, and the remaining connected domains in the motion heat map were conditionally discriminated. If these requirements were met, the domain was included in the road mask. Otherwise, the connected domains were discarded.