Loading...
Publication
Experiences on object tracking using a many-core embedded system
| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 315.58 KB | Adobe PDF |
Advisor(s)
Abstract(s)
Object localization and tracking is core to many practical applications, like human-computer interaction, security and surveillance, robot competitions and Industry 4.0. Such task may be computationally demanding, especially for traditional embedded systems, that usually have tight processing and storage constraints. This calls for the investigation of alternatives, including emergent heterogeneous embedded systems, like the Parallella line of single-board-computers (SBCs).
The work presented in this paper explores the use of a Parallella board with a 16-core Epiphany co-processor, to perform real-time tracking of objects in frames captured by a Kinect sensor, based on color segmentation. We addressed several processing strategies, trying to assess which one performed better. We also ran the same code (where applicable) in several models of the Raspberry Pi platform, for comparison. We conclude that effectively exploring the Epiphany co-processor is not trivial, requiring considerable programming effort and suitable applications (CPU-demanding and highly parallelizable), to the extent that simpler development approaches, on more recent SBCs may be more effective.
Description
Keywords
Visual tracking Computer vision Embedded systems Heterogeneous systems Parallel / hybrid programming
Pedagogical Context
Citation
Minozzo, Laercio; Rufino, José; Lima, José (2017). Experiences on object tracking using a many-core embedded system. In 14th International Conference on Applied Computing (AC). Vilamoura, Portugal. p. 195-204. ISBN 978-989-8533-69-2