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Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories

Sha, Long and Lucey, Patrick and Zheng, Stephan and Kim, Taehwan and Yue, Yisong and Sridharan, Sridha (2017) Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories. . (Submitted)

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We propose a novel method for effective retrieval of multi-agent spatiotemporal tracking data. Retrieval of spatiotemporal tracking data offers several unique challenges compared to conventional text-based retrieval settings. Most notably, the data is fine-grained meaning that the specific location of agents is important in describing behavior. Additionally, the data often contains tracks of multiple agents (e.g., multiple players in a sports game), which generally leads to a permutational alignment problem when performing relevance estimation. Due to the frequent position swap of agents, it is difficult to maintain the correspondence of agents, and such issues make the pairwise comparison problematic for multi-agent spatiotemporal data. To address this issue, we propose a tree-based method to estimate the relevance between multi-agent spatiotemporal tracks. It uses a hierarchical structure to perform multi-agent data alignment and partitioning in a coarse-to-fine fashion. We validate our approach via user studies with domain experts. Our results show that our method boosts performance in retrieving similar sports plays -- especially in interactive situations where the user selects a subset of trajectories compared to current state-of-the-art methods.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Yue, Yisong0000-0001-9127-1989
Additional Information:© 2018 held by the owner/author(s).
Subject Keywords:Retrieval and ranking, Multi-Agent Spatiotemporal Data, Data Alignment
Record Number:CaltechAUTHORS:20190205-113745110
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92673
Deposited By: Tony Diaz
Deposited On:05 Feb 2019 19:47
Last Modified:09 Mar 2020 13:19

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