Special Issue "Bioinspired Computer Vision"
Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 8048
Bioinspired computer vision approaches usually aim to replicate the results obtained by standard algorithms, by using neuromorphic paradigms. The performance obtained by bioinspired approaches is often lower than that of standard algorithms, both in terms of reliability of the results and in terms of speed. Today, there are many computer vision algorithms that are successfully applied in several fields, such as robotics, autonomous navigation, video surveillance, facial recognition, and, more recently, augmented reality. On the other hand, it is well known that biological vision systems are able to extract and analyze the information that is contained in complex, cluttered, and noisy environments, in order to solve vital tasks, such as navigating and recognizing shapes and persons, finding food, or escaping from danger. Biological visual systems are able to perform these tasks with both high sensitivity and strong reliability. Moreover, they are able to solve challenging computational problems, such as scene segmentation, local and global optical flow computation, 3D perception or extracting the meaning of complex objects or movements, in an efficient and quick manner.
The main aim of this Special Issue is to seek high-quality submissions that present and discuss the recent achievements in the development of bioinspired models for solving vision tasks, especially focusing on real-world complex situations and addressing modern benchmarking datasets.
The topics of interest include, but are not limited to the following:
- Bioinspired computer vision for motion and stereo analysis
- Bioinspired computer vision for scene understanding
- Bioinspired computer vision for face, gesture, and shape recognition
- Bioinspired computer vision for the real world: Robustness, learning, adaptability, self-assessment, and failure recovery
- Performance evaluation of bioinspired approaches
- Bioinspired computer vision for surveillance and security applications
- Bioinspired computer vision for virtual and augmented reality applications
- Hardware and high-performance implementations of bioinspired approaches
- Bioinspired computer vision and deep learning
Dr. Manuela Chessa
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