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HMPMR strategy for real-time tracking in aerial images, using direct methods
- Source :
- Machine Vision and Applications. 25:1283-1308
- Publication Year :
- 2014
- Publisher :
- Springer Science and Business Media LLC, 2014.
-
Abstract
- The vast majority of approaches make use of features to track objects. In this paper, we address the tracking problem with a tracking-by-registration strategy based on direct methods. We propose a hierarchical strategy in terms of image resolution and number of parameters estimated in each resolution, that allows direct methods to be applied in demanding real-time visual-tracking applications. We have called this strategy the Hierarchical Multi-Parametric and Multi-Resolution strategy (HMPMR). The Inverse Composition Image Alignment Algorithm (ICIA) is used as an image registration technique and is extended to an HMPMR-ICIA. The proposed strategy is tested with different datasets and also with image data from real flight tests using an Unmanned Aerial Vehicle, where the requirements of direct methods are easily unsatisfied (e.g. vehicle vibrations). Results show that using an HMPMR approach, it is possible to cope with the efficiency problem and with the small motion constraint of direct methods, conducting the tracking task at real-time frame rates and obtaining a performance that is comparable to, or even better than, the one obtained with the other algorithms that were analyzed.
- Subjects :
- Computer science [C05] [Engineering, computing & technology]
business.industry
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Communications Engineering, Networks
Image registration
Pattern Recognition
Sciences informatiques [C05] [Ingénierie, informatique & technologie]
Tracking (particle physics)
Frame rate
Computer Science Applications
Image (mathematics)
Image Processing and Computer Vision
Hardware and Architecture
Direct methods
Pattern recognition (psychology)
Eye tracking
Computer vision
Computer Vision and Pattern Recognition
Artificial intelligence
business
Image resolution
Software
Subjects
Details
- ISSN :
- 14321769 and 09328092
- Volume :
- 25
- Database :
- OpenAIRE
- Journal :
- Machine Vision and Applications
- Accession number :
- edsair.doi.dedup.....1f9f51039f149dbe1711a8ac4da69fc3
- Full Text :
- https://doi.org/10.1007/s00138-014-0617-2