Showing papers by "Diego B. Haddad published in 2022"
4 citations
TL;DR: In this article , the authors present a comprehensive method for direct georeferencing of aerial images acquired by cameras mounted on UAS, where all required information, mathematical operations and implementation steps are explained in detail.
Abstract: Optical image sensors are the most common remote sensing data acquisition devices present in Unmanned Aerial Systems (UAS). In this context, assigning a location in a geographic frame of reference to the acquired image is a necessary task in the majority of the applications. This process is denominated direct georeferencing when ground control points are not used. Despite it applies simple mathematical fundamentals, the complete direct georeferencing process involves much information, such as camera sensor characteristics, mounting measurements, attitude and position of the UAS, among others. In addition, there are many rotations and translations between the different reference frames, among many other details, which makes the whole process a considerable complex operation. Another problem is that manufacturers and software tools may use different reference frames posing additional difficulty when implementing the direct georeferencing. As this information is spread among many sources, researchers may face difficulties on having a complete vision of the method. In fact, there is absolutely no paper in the literature that explain this process in a comprehensive way. In order to supply this implicit demand, this paper presents a comprehensive method for direct georeferencing of aerial images acquired by cameras mounted on UAS, where all required information, mathematical operations and implementation steps are explained in detail. Finally, in order to show the practical use of the method and to prove its accuracy, both simulated and real flights were performed, where objects of the acquired images were georeferenced.
3 citations
2 citations
TL;DR: In this article , a deterministic and stochastic model is proposed to predict various learning characteristics of the LMS algorithm with coefficient reuse, which is able to improve the steady-state performance of adaptive filter algorithms, especially in very challenging low signal-to-noise scenarios.
TL;DR: This work proposes an approach based on memetic algorithm concepts to find high-quality solutions to the Sensor Allocation Problem, where each node can be associated with one of four operation modes (classified according to its maximum range).
01 Jan 2022
TL;DR: In this paper , a long-term person ReID system using face recognition is presented to emphasize current techniques' limitations, and an outlook on longterm person reidentification, an emerging research topic regarding when consecutive acquisitions of an individual can be found apart for days or even months.
Abstract: AbstractPerson reidentification, i.e., retrieving a person of interest across several non-overlapping cameras, is a task that is far from trivial. Despite its great commercial value and wide range of applications (e.g., surveillance, intelligent environments, forensics, service robotics, marketing), it remains unsolved, even when the individuals do not change clothes during the recognition period. This paper provides an outlook on long-term person reidentification, an emerging research topic regarding when consecutive acquisitions of an individual can be found apart for days or even months, making such a task even more challenging. A long-term reidentification system using face recognition is presented to emphasize current techniques’ limitations.KeywordsLong-term person ReIDDeep learningComputer visionMultimodal retrieval