Efficient Motion Estimation for Remotely Controlled Vehicles: A Novel Algorithm Leveraging User Interaction
Source abstract
Abstract
Unmanned Aerial Vehicles (UAVs) are increasingly being used in a variety of applications, including entertainment, surveillance, and delivery. However, the real-time Motion Estimation (ME) of UAVs is challenging due to the high speed and unpredictable movements of these vehicles. This paper presents a novel algorithm for optimizing ME for Remotely Controlled Vehicles (RCVs), with a particular focus on UAVs. The proposed algorithm, called Motion Dynamics Input Search (MDIS), incorporates information from vehicle motion dynamics estimation to enhance the accuracy and efficiency of ME. The MDIS algorithm addresses the challenges associated with real-time ME in RCVs by leveraging user input to guide the search for the most similar blocks in the previous video frame. Through extensive experimentation and evaluation, this study demonstrates the effectiveness of the proposed algorithm in improving ME performance for RCVs. The findings highlight the potential impact of user interaction and motion dynamics estimation in shaping the future of ME algorithms for RCVs and similar applications.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Video Surveillance and Tracking Methods · Video Coding and Compression Technologies · Advanced Vision and Imaging
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia
Funding
EU
References (27)
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