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The human visual system employs an information selection mechanism, visual attention, so that higher-level cognitive processes can be restricted to a potentially important subset of the incoming information. This mechanism is amenable to efficient computational implementation and, consequently, it has been incorporated into many technological applications. Among these applications is autonomous mobile...
Vision is a potent source of information, not just for humans, but for robots as well. Processing visual information is a computationally expensive task, one that is often difficult to accomplish in real-time on embedded hardware. In the broad field of visual research exists egomotion estimation, the process of determining self-motion from optical flow. Here we show a technological adaptation and...
In this work, a clustering approach to obtain compact topological models of an environment is developed and evaluated. The usefulness of these models is tested by studying their utility to solve the robot localization problem subsequently. Omnidirectional visual information and global appearance descriptors are used both to create and compress the models and to estimate the position of the robot....
Landmarks can be used as a reference to enable people or robots to localize themselves or to navigate in their environment. Automatic definition and extraction of appropriate landmarks from the environment has proven to be a challenging task when pre-defined landmarks are not present. We propose a novel computational model of automatic landmark detection from a single image without any pre-defined...
In robotic navigation, biologically inspired localization models have often exhibited interesting features and proven to be competitive with other solutions in terms of adaptability and performance. In general, place recognition systems rely on global or local visual descriptors; or both. In this paper, we propose a model of context-based place cells combining these two information. Global visual...
Knowledge of the physical properties of objects is essential in a wide range of robotic manipulation scenarios. A robot may not always be aware of such properties prior to interaction. If an object is incorrectly assumed to be rigid, it may exhibit unpredictable behavior when grasped. In this paper, we use vision based observation of the behavior of an object a robot is interacting with and use it...
This paper is concerned with the interpretation of visual information for robot localization. It presents a probabilistic localization system that generates an appropriate observation model online, unlike existing systems which require pre-determined belief models. This paper proposes that probabilistic visual localization requires two major operating modes - one to match locations under similar conditions...
Development of intellectual information technology augmented reality for persons with disabilities, including converting visual images into sound and vice versa by generating a single concept. Use of the unified knowledge base for operating mechanism, that stores images concepts.
In this paper, we introduce a non-verbal multimodal joint visual attention model for human-robot interaction in household scenarios. Our model combines the bottom-up saliency and depth-based segmentation with the top-down cues such as pointing and gaze to detect the objects of interest according to the user. For generation of the top-down saliency maps, we have introduced novel methods for object...
Robust, scalable localization unlocks path-planning, obstacle avoidance as well as manipulation and thus is a core competency for many robotic applications. However, as we leave the lab and move out in the world, models of the environment no longer span distances of meters but kilometers in length. Now, gigabytes instead of megabytes of memory are required to hold the model of the environment required...
Therapy environments for robot-assisted stroke rehabilitation are mostly static, in that objects are earmarked for different functional tasks, object locations remain fixed, trajectories are predefined and tasks manually selected. This work advocates the need for a therapy environment that allows dynamic object positioning, different objects can be used for the same functional task and tasks can be...
Designing technological systems for personalized education is an iterative and interdisciplinary process that demands a deep understanding of the application domain, the limitations of current methods and technologies, and the computational methods and complexities behind user modeling and adaptation. We present our design process and the Socially Assistive Robot (SAR) tutoring system to support the...
Humanoid robots have complex kinematic chains that are difficult to model with the precision required to reach and/or grasp objects properly. In this paper we propose a GPU-enabled vision based 3D hand pose estimation method that runs during robotic reaching tasks to calibrate in real time the kinematic chain of the robot arm. This is achieved by combining: i) proprioceptive and visual sensing, and...
For smooth interaction between human and robot, the robot should have an ability to manipulate human attention and behaviors. In this study, we developed a visual attention model for manipulating human attention by a robot. The model consists of two modules, such as the saliency map generation module and manipulation map generation module. The saliency map describes the bottom-up effect of visual...
The task of visual vocabulary construction plays an important role in the bag-of-words based pattern analysis and robotic applications. A discriminative vocabulary generation in unsupervised case is an open issue for reducing perceptual aliasing in image matching based applications. In this paper, we present a scheme to evaluate the discriminative power of each visual word quantitatively in terms...
The visualization of the coronary vasculature is of utmost importance in interventional cardiology. Intravascular surgical robots assist the practitioners to perform the complex procedure while protecting them from the tremendous occupational hazards. Robotic surgical simulation aims to provide support for the learners in both efficiency and convenience. The blood vessels especially the coronary arteries...
Map matching is a fundamental task in many robot vision applications, including viewpoint localization, change detection, alignment, merging, segmentation of maps, and multi-robot mapping. Existing frameworks so far have concentrated on local feature-based approach, where discriminative local features are extracted from the maps and visual indexing and map database searched are performed to find correspondence...
We present a teleoperation system which supports foveated multi-resolution, wide field of view visual feedback. In the proposed system, a saliency-based visual attention system is implemented to simulate human visual system and to help determine the candidate visual attention area automatically. We link the visual attention system and the foveated multi-resolution image compression system to realize...
This paper presents a novel, biologically-inspired, approach for an efficient management of computational resources for visual processing. In particular, we modulate a visual “attentional landscape” with the motor plans of a robot. The attentional landscape is a more recent, general and a more complex concept of an arrangement of spatial attention than a simple “attentional spotlight” or a “zoom-lens”...
Map matching is a critical problem of robotic mapping and localization which has attracted broad interests in robot vision community. Despite its accuracy and efficiency, the popular RANSAC-based algorithm suffers from large memory requirements, which is proportional to the number N and size of maps. In this paper, our goal is to realize fast succinct map matching by introducing a part-based scene...
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