105 resultados para deformable object


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With the emergence of multi-cores into the mainstream, there is a growing need for systems to allow programmers and automated systems to reason about data dependencies and inherent parallelismin imperative object-oriented languages. In this paper we exploit the structure of object-oriented programs to abstract computational side-effects. We capture and validate these effects using a static type system. We use these as the basis of sufficient conditions for several different data and task parallelism patterns. We compliment our static type system with a lightweight runtime system to allow for parallelization in the presence of complex data flows. We have a functioning compiler and worked examples to demonstrate the practicality of our solution.

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The paper presents a fast and robust stereo object recognition method. The method is currently unable to identify the rotation of objects. This makes it very good at locating spheres which are rotationally independent. Approximate methods for located non-spherical objects have been developed. Fundamental to the method is that the correspondence problem is solved using information about the dimensions of the object being located. This is in contrast to previous stereo object recognition systems where the scene is first reconstructed by point matching techniques. The method is suitable for real-time application on low-power devices.

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Intelligent surveillance systems typically use a single visual spectrum modality for their input. These systems work well in controlled conditions, but often fail when lighting is poor, or environmental effects such as shadows, dust or smoke are present. Thermal spectrum imagery is not as susceptible to environmental effects, however thermal imaging sensors are more sensitive to noise and they are only gray scale, making distinguishing between objects difficult. Several approaches to combining the visual and thermal modalities have been proposed, however they are limited by assuming that both modalities are perfuming equally well. When one modality fails, existing approaches are unable to detect the drop in performance and disregard the under performing modality. In this paper, a novel middle fusion approach for combining visual and thermal spectrum images for object tracking is proposed. Motion and object detection is performed on each modality and the object detection results for each modality are fused base on the current performance of each modality. Modality performance is determined by comparing the number of objects tracked by the system with the number detected by each mode, with a small allowance made for objects entering and exiting the scene. The tracking performance of the proposed fusion scheme is compared with performance of the visual and thermal modes individually, and a baseline middle fusion scheme. Improvement in tracking performance using the proposed fusion approach is demonstrated. The proposed approach is also shown to be able to detect the failure of an individual modality and disregard its results, ensuring performance is not degraded in such situations.

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Within a surveillance video, occlusions are commonplace, and accurately resolving these occlusions is key when seeking to accurately track objects. The challenge of accurately segmenting objects is further complicated by the fact that within many real-world surveillance environments, the objects appear very similar. For example, footage of pedestrians in a city environment will consist of many people wearing dark suits. In this paper, we propose a novel technique to segment groups and resolve occlusions using optical flow discontinuities. We demonstrate that the ratio of continuous to discontinuous pixels within a region can be used to locate the overlapping edges, and incorporate this into an object tracking framework. Results on a portion of the ETISEO database show that the proposed algorithm results in improved tracking performance overall, and improved tracking within occlusions.

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Several studies have developed metrics for software quality attributes of object-oriented designs such as reusability and functionality. However, metrics which measure the quality attribute of information security have received little attention. Moreover, existing security metrics measure either the system from a high level (i.e. the whole system’s level) or from a low level (i.e. the program code’s level). These approaches make it hard and expensive to discover and fix vulnerabilities caused by software design errors. In this work, we focus on the design of an object-oriented application and define a number of information security metrics derivable from a program’s design artifacts. These metrics allow software designers to discover and fix security vulnerabilities at an early stage, and help compare the potential security of various alternative designs. In particular, we present security metrics based on composition, coupling, extensibility, inheritance, and the design size of a given object-oriented, multi-class program from the point of view of potential information flow.

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Refactoring focuses on improving the reusability, maintainability and performance of programs. However, the impact of refactoring on the security of a given program has received little attention. In this work, we focus on the design of object-oriented applications and use metrics to assess the impact of a number of standard refactoring rules on their security by evaluating the metrics before and after refactoring. This assessment tells us which refactoring steps can increase the security level of a given program from the point of view of potential information flow, allowing application designers to improve their system’s security at an early stage.