What features of video processing differ from image processing?

Video processing, compared to images, has several features:

• Temporal component: Video is a sequence of frames, so it’s important to consider temporal dynamics and relationships between frames (e.g., object movement).

• Larger data volume: Video contains many frames, requiring more resources for storage and processing.

• Use of sequence analysis methods: For video, recurrent neural networks (RNN, LSTM), 3D convolutions, or transformers are used, which take into account temporal information.

• Stabilization and motion compensation: Often, it’s necessary to compensate for camera or object movement to analyze scenes correctly.

• Audio processing: In some tasks, video analysis includes the audio track, adding a multimodal aspect.

• Specific tasks: For example, event detection, object tracking, action recognition — tasks not present in static images.

• Quality issues: Video may contain motion blur, noise, lighting changes, which complicate processing.

Thus, working with video requires integrating spatial and temporal information, as well as optimizing computations for large data volumes.