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An overview on the evaluated video retrieval tasks at TRECVID 2022
The TREC Video Retrieval Evaluation (TRECVID) is a TREC-style video analysis and retrieval evaluation with the goal of promoting progress in research and development of content-based exploitation and retrieval of information from digital video via open, tasks-based evaluation supported by metrology.
Damage Estimation and Localization from Sparse Aerial Imagery
The approach is based on using structure from motion to relate image coordinates to world coordinates via a projective transformation, using class activation mapping to detect the extent of damage in an image, and applying the projective transformation to localize damage in world coordinates.
TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains
In total, 29 teams from various research organizations worldwide completed one or more of the following six tasks: 1.
Large Scale Organization and Inference of an Imagery Dataset for Public Safety
Video applications and analytics are routinely projected as a stressing and significant service of the Nationwide Public Safety Broadband Network.
Semantic Analysis of Traffic Camera Data: Topic Signal Extraction and Anomalous Event Detection
In this article, we propose a semantics-oriented approach to analyzing sequential image data, and demonstrate its application for automatic detection of real-world, anomalous events in weather and traffic conditions.
Semantic Topic Analysis of Traffic Camera Images
This study demonstrates the flexibility of our approach, which allows us to analyze weather events and freeway traffic using only traffic camera image labels.
