Areas activated during naturalistic reading comprehension overlap topological visual, auditory, and somatotomotor maps

Cortical mapping techniques using fMRI have been instrumental in identifying the boundaries of topological (neighbor-preserving) maps in early sensory areas. The presence of topological maps beyond early sensory areas raises the possibility that they might play a significant role in other cognitive systems, and that topological mapping might help to delineate areas involved in higher cognitive processes. In this study, we combine surface-based visual, auditory, and somatomotor mapping methods with a naturalistic reading comprehension task in the same group of subjects to provide a qualitative and quantitative assessment of the cortical overlap between sensory-motor maps in all major sensory modalities, and reading processing regions. Our results suggest that cortical activation during naturalistic reading comprehension overlaps more extensively with topological sensory-motor maps than has been heretofore appreciated. Reading activation in regions adjacent to occipital lobe and inferior parietal lobe almost completely overlaps visual maps, whereas a significant portion of frontal activation for reading in dorsolateral and ventral prefrontal cortex overlaps both visual and auditory maps. Even classical language regions in superior temporal cortex are partially overlapped by topological visual and auditory maps. By contrast, the main overlap with somatomotor maps is restricted to a small region on the anterior bank of the central sulcus near the border between the face and hand representations of M-I

Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps

Visual robot navigation within large-scale, semi-structured environments deals with various challenges such as computation intensive path planning algorithms or insufficient knowledge about traversable spaces. Moreover, many state-of-the-art navigation approaches only operate locally instead of gaining a more conceptual understanding of the planning objective. This limits the complexity of tasks a robot can accomplish and makes it harder to deal with uncertainties that are present in the context of real-time robotics applications. In this work, we present Topomap, a framework which simplifies the navigation task by providing a map to the robot which is tailored for path planning use. This novel approach transforms a sparse feature-based map from a visual Simultaneous Localization And Mapping (SLAM) system into a three-dimensional topological map. This is done in two steps. First, we extract occupancy information directly from the noisy sparse point cloud. Then, we create a set of convex free-space clusters, which are the vertices of the topological map. We show that this representation improves the efficiency of global planning, and we provide a complete derivation of our algorithm. Planning experiments on real world datasets demonstrate that we achieve similar performance as RRT* with significantly lower computation times and storage requirements. Finally, we test our algorithm on a mobile robotic platform to prove its advantages.Comment: 8 page

A framework for automatic and perceptually valid facial expression generation

Facial expressions are facial movements reflecting the internal emotional states of a character or in response to social communications. Realistic facial animation should consider at least two factors: believable visual effect and valid facial movements. However, most research tends to separate these two issues. In this paper, we present a framework for generating 3D facial expressions considering both the visual the dynamics effect. A facial expression mapping approach based on local geometry encoding is proposed, which encodes deformation in the 1-ring vector. This method is capable of mapping subtle facial movements without considering those shape and topological constraints. Facial expression mapping is achieved through three steps: correspondence establishment, deviation transfer and movement mapping. Deviation is transferred to the conformal face space through minimizing the error function. This function is formed by the source neutral and the deformed face model related by those transformation matrices in 1-ring neighborhood. The transformation matrix in 1-ring neighborhood is independent of the face shape and the mesh topology. After the facial expression mapping, dynamic parameters are then integrated with facial expressions for generating valid facial expressions. The dynamic parameters were generated based on psychophysical methods. The efficiency and effectiveness of the proposed methods have been tested using various face models with different shapes and topological representations

Cognition and maps : reading and scene comprehension extensively overlap topological viusal, auditory and somatomotor maps in the human cortex

Cortical mapping techniques using fMRI have been instrumental in identifying the boundaries of topological maps in early sensory areas. The presence of topological maps beyond early sensory areas raises the possibility that they might play a significant role in other cognitive systems, and that topological mapping might help to delineate areas involved in higher cognitive processes. This thesis investigates the three way interplay between the full extent of topologically mapped sensory-motor regions (detected using retinotopic, tonotopic and somatomotor mapping) and activation observed during two high level comprehension specific tasks in the same set of subjects across the whole cortex. In the first set of studies, I combined surface based visual, auditory, and somatomotor mapping methods with a naturalistic reading comprehension task to provide a qualitative and quantitative assessment of the cortical overlap between sensory-motor maps in all major modalities, and reading processing regions. The results suggest that cortical activation during naturalistic reading comprehension overlaps more extensively with topological sensorymotor maps than has been heretofore appreciated. To further differentiate the activations observed during the reading study, a separate fMRI study involving a purely picture-based narrative scene comprehension task was carried out on the same set of subjects. The results from the cumulative dataset suggest that the reading and scene activations are centred around the same regions in the occipito-parietal, temporal and frontal cortex. The shared activations between reading and scene also largely overlap with topological cortical maps. Additionally, there are regions overlapping with maps in occipito-parietal, temporal and frontal cortex that are distinct to either reading or scene processing. Finally, the mapping studies also identified several previously unreported maps in the cortex including a visual and a tonotopic map in the cingulate cortex, and several tonotopic maps in the frontal cortex

Keyframe-based monocular SLAM: design, survey, and future directions

Extensive research in the field of monocular SLAM for the past fifteen years has yielded workable systems that found their way into various applications in robotics and augmented reality. Although filter-based monocular SLAM systems were common at some time, the more efficient keyframe-based solutions are becoming the de facto methodology for building a monocular SLAM system. The objective of this paper is threefold: first, the paper serves as a guideline for people seeking to design their own monocular SLAM according to specific environmental constraints. Second, it presents a survey that covers the various keyframe-based monocular SLAM systems in the literature, detailing the components of their implementation, and critically assessing the specific strategies made in each proposed solution. Third, the paper provides insight into the direction of future research in this field, to address the major limitations still facing monocular SLAM; namely, in the issues of illumination changes, initialization, highly dynamic motion, poorly textured scenes, repetitive textures, map maintenance, and failure recovery