Construction of all-in-focus images assisted by depth sensing

Multi-focus image fusion is a technique for obtaining an all-in-focus image in which all objects are in focus to extend the limited depth of field (DoF) of an imaging system. Different from traditional RGB-based methods, this paper presents a new multi-focus image fusion method assisted by depth sensing. In this work, a depth sensor is used together with a color camera to capture images of a scene. A graph-based segmentation algorithm is used to segment the depth map from the depth sensor, and the segmented regions are used to guide a focus algorithm to locate in-focus image blocks from among multi-focus source images to construct the reference all-in-focus image. Five test scenes and six evaluation metrics were used to compare the proposed method and representative state-of-the-art algorithms. Experimental results quantitatively demonstrate that this method outperforms existing methods in both speed and quality (in terms of comprehensive fusion metrics). The generated images can potentially be used as reference all-in-focus images.Comment: 18 pages. This paper has been submitted to Computer Vision and Image Understandin

Remote Sensing Information Sciences Research Group, Santa Barbara Information Sciences Research Group, year 3

Research continues to focus on improving the type, quantity, and quality of information which can be derived from remotely sensed data. The focus is on remote sensing and application for the Earth Observing System (Eos) and Space Station, including associated polar and co-orbiting platforms. The remote sensing research activities are being expanded, integrated, and extended into the areas of global science, georeferenced information systems, machine assissted information extraction from image data, and artificial intelligence. The accomplishments in these areas are examined

Assistance strategies for robotized laparoscopy

Robotizing laparoscopic surgery not only allows achieving better accuracy to operate when a scale factor is applied between master and slave or thanks to the use of tools with 3 DoF, which cannot be used in conventional manual surgery, but also due to additional informatic support. Relying on computer assistance different strategies that facilitate the task of the surgeon can be incorporated, either in the form of autonomous navigation or cooperative guidance, providing sensory or visual feedback, or introducing certain limitations of movements. This paper describes different ways of assistance aimed at improving the work capacity of the surgeon and achieving more safety for the patient, and the results obtained with the prototype developed at UPC.Peer ReviewedPostprint (author's final draft

Simultaneous Feature and Body-Part Learning for Real-Time Robot Awareness of Human Behaviors

Robot awareness of human actions is an essential research problem in robotics with many important real-world applications, including human-robot collaboration and teaming. Over the past few years, depth sensors have become a standard device widely used by intelligent robots for 3D perception, which can also offer human skeletal data in 3D space. Several methods based on skeletal data were designed to enable robot awareness of human actions with satisfactory accuracy. However, previous methods treated all body parts and features equally important, without the capability to identify discriminative body parts and features. In this paper, we propose a novel simultaneous Feature And Body-part Learning (FABL) approach that simultaneously identifies discriminative body parts and features, and efficiently integrates all available information together to enable real-time robot awareness of human behaviors. We formulate FABL as a regression-like optimization problem with structured sparsity-inducing norms to model interrelationships of body parts and features. We also develop an optimization algorithm to solve the formulated problem, which possesses a theoretical guarantee to find the optimal solution. To evaluate FABL, three experiments were performed using public benchmark datasets, including the MSR Action3D and CAD-60 datasets, as well as a Baxter robot in practical assistive living applications. Experimental results show that our FABL approach obtains a high recognition accuracy with a processing speed of the order-of-magnitude of 10e4 Hz, which makes FABL a promising method to enable real-time robot awareness of human behaviors in practical robotics applications.Comment: 8 pages, 6 figures, accepted by ICRA'1

Land Use Changes and Their Perception in the Hinterland of Barranquilla, Colombian Caribbean

The coastal strip of the western peri-urban area of Barranquilla in the Atlántico Department (Colombia) is experiencing changes in human-environment interactions through infrastructure, residential, and tourism projects in a vulnerable landscape. In the hilly area, fragments of biodiverse tropical dry forest still exist in various states of conservation and degradation. To understand the interrelated social, economic, and ecological transformations in the area, we analyzed land use change on the local scale including the local community’s perception, because the local community is a key actor for sustainable land use. For the analysis of the interrelated social, economic, and ecological processes, we combined visual interpretation of high-resolution satellite imagery, on-site field land use mapping, and a spatial statistical analysis of the distribution of land use classes with in-depth interviews and a participatory GIS workshop, thus benefitting from the complementary methodological strengths of these approaches. The case study is the rural community of El Morro, which exhibits the typical social, economic, and ecological changes of the coastal strip of the western peri-urban area of Barranquilla. The local community perceives a continuous loss of forest area, but observations from on-site field mapping cannot confirm this linear trend. We observed a gradual replacement of traditional land uses such as smallholder agriculture, charcoal production, and cattle breeding by services for tourism, gated community projects for urban dwellers, and infrastructure projects; these spatial developments have several characteristics of rural gentrification. We conclude that the drivers of environmental degradation have changed and the degradation increased. The development projects of external companies have been rejected by the local community and have induced environmental consciousness among community members. Thus, the local community has become an advocate for sustainable land use in the study area