Evolving Head Tracking Routines With Brain Programming
| Autor: | Daniel E. Hernández, Eddie Clemente, Mariana Chan-Ley, Gustavo Olague |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
General Computer Science
Computer science Feature extraction Normalization (image processing) 02 engineering and technology Automatic programming 0202 electrical engineering electronic engineering information engineering General Materials Science Saliency map Computer vision learning business.industry Binary image Deep learning General Engineering Process (computing) deep learning brain modeling 020207 software engineering deep genetic programming Visualization Eye tracking 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering Artificial intelligence business optimization lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 6, Pp 26254-26270 (2018) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2018.2831633 |
| Popis: | Visual tracking has long been studied in computer vision, and it has many practical applications such as surveillance and security, traffic control, human-computer interaction, and activity or behavior recognition to mention but a few. Head tracking attempts to follow a person's head within a video sequence. This paper presents a methodology that automatically designs an artificial dorsal stream for the problem of head tracking. Multiple visual operators are synthesized to obtain several visual and conspicuity maps that are fused into a saliency map, which is converted to a binary image, thus defining the proto-object. The automatic design of visual attention programs for the problem of head tracking is achieved through an optimization process following the Darwinian paradigm of artificial evolution. Artificial brains are synthesized using multiple visual operators embedded within a complex hierarchical procedure consisting of several key processes such as center-surround mechanisms, normalization, and pyramid-scale processes. The proposed strategy robustly handles many difficulties including occlusion, distraction, and illumination, and the resulting programs are real-time systems that are able to track a person's head with enough accuracy to automatically control the camera. Extensive experimentation shows that the proposed method outperforms several state-of-the-art methods in the challenging problem of head tracking. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|