TennisVid2Text: Fine-grained Descriptions for Domain Specific Videos
This work addresses the challenge of generating rich, domain-specific video descriptions for sports broadcasting, though it is incremental as it focuses on a narrow domain.
The paper tackles the problem of generating fine-grained textual descriptions for broadcast tennis videos, aiming to produce expert-like commentary by leveraging a large corpus of human-created descriptions and evaluating on a new dataset, with results addressing semantic correctness and readability.
Automatically describing videos has ever been fascinating. In this work, we attempt to describe videos from a specific domain - broadcast videos of lawn tennis matches. Given a video shot from a tennis match, we intend to generate a textual commentary similar to what a human expert would write on a sports website. Unlike many recent works that focus on generating short captions, we are interested in generating semantically richer descriptions. This demands a detailed low-level analysis of the video content, specially the actions and interactions among subjects. We address this by limiting our domain to the game of lawn tennis. Rich descriptions are generated by leveraging a large corpus of human created descriptions harvested from Internet. We evaluate our method on a newly created tennis video data set. Extensive analysis demonstrate that our approach addresses both semantic correctness as well as readability aspects involved in the task.