Title Download Published at Year
Real time vision for robotics using a moving fovea approach with multi resolution

Rafael Beserra Gomes , Bruno Motta de Carvalho , Luiz Marcos

We propose a new approach to reduce and abstract visual data useful for robotics applications. Basically, a moving Fovea in combination with a multi-resolution representation is created from a pair of input images given by a stereo head, that reduces hundreds of times the amount of information from the original images. With this new theoretical approach we are able to compute several feature maps, including several filters, stereo matching, and motion, in real time, that is at more than 30 frames per second. As the main contribution, the moving fovea allows, most of the time, a robot to avoid performing physical motion with the cameras in order to get a desirable region in the images center. We present mathematical formalization of the moving Fovea approach, the algorithms, and details of the implementation of such schema. We validate it with experimental results. This approach has demonstrated to be very useful to robotics vision.
ICRA 2008
Real Time Image Segmentation Using User Indicated real-world Seeds

Rafael Beserra Gomes , Rafael Vidal Aroca , Bruno Motta de Carvalho , Luiz Marcos

We propose a novel and fast interactive segmentation methodology for computer vision applications. Basically, the proposed system performs the tracking of seeds so that multiple seeds can be acquired over time, substantially improving the segmentation results. Moreover, instead of image coordinates, the user indicates points in the real-world that become seeds in the image. These seeds can be indicated, for example using a laser pointer or a smart-phone. The seeds can then be tracked and used by a segmentation algorithm. Experiments using the Lucas-Kanade Optical Flow and the Fast Multi-Object Fuzzy Segmentation (Fast-MOFS) algorithm demonstrate that the proposed technique successfully segments images in real-time and improves the user ability to directly segment an object in the real world. The proposed system has a high performance, allowing it to be used with high frame rates in devices with low processing capability and/or with restricted power requirements.
Method for Reading Sensors and Controlling Actuators Using Audio Interfaces of Mobile Devices

Rafael Vidal Aroca , Aquiles , Luiz Marcos

This article presents a novel closed loop control architecture based on audio channels of several types of computing devices, such as mobile phones and tablet computers, but not restricted to them. The communication is based on an audio interface that relies on the exchange of audio tones, allowing sensors to be read and actuators to be controlled. As an application example, the presented technique is used to build a low cost mobile robot, but the system can also be used in a variety of mechatronics applications and sensor networks, where smartphones are the basic building blocks.
Sensors 2012
Increasing Students' Interest With Low-Cost CellBots

Rafael Vidal Aroca , Rafael Beserra Gomes , ,

This paper introduces the use of a flexible and affordable educational robot specifically developed for the practical experimentation inherent to technological disciplines. The robot has been designed to be reconfigurable and extendible, serving as an experimental platform across several undergraduate courses. As most students have a mobile cell phone, this was used as the main control computer for the so-called CellBot, thus avoiding any need to deal with the details of microcontrollers or other embedded computing devices. Assessment results are also presented, based on a pre- and post-survey of student opinion administered to 204 science and engineering students from several universities. Among the conclusions are that 83% of the students prefer to use these low-cost robots as tools to improve their learning of the theory in several disciplines, and 71% of the students stated that they prefer to have their own robot to experiment with, instead of using a didactic kit loaned to them by the university.
IEEE Transaction on Education 2012
Visual identification of medicine boxes using features matching

Xiankleber Benjamin , Rafael Beserra Gomes , Aquiles , Luiz Marcos

This paper proposes to use visual features matching in the identification of medicine boxes for visually impaired people. We use a camera device, available in several popular devices such as computers, televisions and cell phones, to identify relevant features on medicine box. After box detection, audio files are played to inform about dosage, indications and contraindications of the medication. Making use of this vision system can help many visually impaired people to take the right medicine at the time indicated in advance by the doctor. Experiments with 15 blindfolded volunteers demonstrated that 93% of them believes that the system was useful or very useful to identify the medicine boxes.
Visual Attention Guided Features Selection with Foveated Images

Rafael Beserra Gomes , Bruno Motta de Carvalho , Luiz Marcos

Visual attention is a very important task in autonomous robotics, but, because of its complexity, the processing time required is significant. We propose an architecture for feature selection using foveated images that is guided by visual attention tasks and that reduces the processing time required to perform these tasks. Our system can be applied in bottom–up or top–down visual attention. The foveated model determines which scales are to be used on the feature extraction algorithm. The system is able to discard features that are not extremely necessary for the tasks, thus, reducing the processing time. If the fovea is correctly placed, then it is possible to reduce the processing time without compromising the quality of the tasks' outputs. The distance of the fovea from the object is also analyzed. If the visual system loses the tracking in top–down attention, basic strategies of fovea placement can be applied. Experiments have shown that it is possible to reduce up to 60% the processing time with this approach. To validate the method, we tested it with the feature algorithm known as speeded up robust features (SURF), one of the most efficient approaches for feature extraction. With the proposed architecture, we can accomplish real time requirements of robotics vision, mainly to be applied in autonomous robotics.
Neurocomputing 2013
Efficient 3D object recognition using foveated point clouds

Rafael Beserra Gomes , Bruno Marques da Silva , Renato Gardiman , Rafael Vidal Aroca , Lourena Rocha Medeiros , Luiz Marcos

Recent hardware technologies have enabled acquisition of 3D point clouds from real world scenes in real time. A variety of interactive applications with the 3D world can be developed on top of this new technological scenario. However, a main problem that still remains is that most processing techniques for such 3D point clouds are computationally intensive, requiring optimized approaches to handle such images, especially when real time performance is required. As a possible solution, we propose the use of a 3D moving fovea based on a multiresolution technique that processes parts of the acquired scene using multiple levels of resolution. Such approach can be used to identify objects in point clouds with efficient timing. Experiments show that the use of the moving fovea shows a seven fold performance gain in processing time while keeping 91.6% of true recognition rate in comparison with state-of-the-art 3D object recognition methods.
Computers & Graphics 2013