Recognition systems are systems and procedures that extract higher-level information and knowledge about entities in the real world from incoming data or assist humans in doing so.
The main focus of IOSB’s activities lies on researching and developing recognition systems based on imaging sensors. We employ imaging sensors covering the visual as well as the IR spectral ranges, which are processed as single images or video image sequences. The real-time aspect and process optimization for lightweight hardware and application-specific solutions play a major role in our work. Our recognition methods are primarily deep learning approaches, which are adapted or developed specifically to fit the task. We train and evaluate our models on our own, extensive deep learning server infrastructure. While we have a wide range of annotated datasets already available for training, we have also established an efficient process for curating and annotating additional training data using several tools and workflows developed specifically for this process.