60451548
Switching Hypothesized Measurements: A Dynamic Model with Applications to Occlusion Adaptive Joint Tracking
This paper proposes a dynamic model supporting multimodal state space probability distributions and presents the application of the model in dealing with visual occlusions when tracking multiple objects jointly. For a set of hypotheses, multiple measurements are acquired at each time instant. The model switches among a set of hypothesized measurements during the propagation. Two computationally efficient filtering algorithms are derived for online joint tracking. Both the occlusion relationship and state of the objects are recursively estimated from the history of measurement data. The switching hypothesized measurements (SHM) model is generally applicable to describe various dynamic processes with multiple alternative measurement methods.
6934721
A dynamic conditional random field model for foreground and shadow segmentation
This paper proposes a dynamic conditional random field (DCRF) model for foreground object and moving shadow segmentation in indoor video scenes. Given an image sequence, temporal dependencies of consecutive segmentation fields and spatial dependencies within each segmentation field are unified by a dynamic probabilistic framework based on the conditional random field (CRF). An efficient approximate filtering algorithm is derived for the DCRF model to recursively estimate the segmentation field from the history of observed images. The foreground and shadow segmentation method integrates both intensity and gradient features. Moreover, models of background, shadow, and gradient information are updated adaptively for nonstationary background processes. Experimental results show that the proposed approach can accurately detect moving objects and their cast shadows even in monocular grayscale video sequences.
8808466
Joint region tracking with switching hypothesized measurements
We propose a switching hypothesized measurements (SHM) model supporting multimodal probability distributions and present the application of the model in handling potential variability in visual environments when tracking multiple objects jointly. For a set of occlusion hypotheses, a frame is measured once under each hypothesis, resulting in a set of measurements at each time instant. A computationally efficient SHM filter is derived for online joint region tracking. Both occlusion relationships and states of the objects are recursively estimated from the history of hypothesized measurements. The reference image is updated adaptively to deal with appearance changes of the objects. The SHM model is generally applicable to various dynamic processes with multiple alternative measurement methods.
14783345
Designing of LED Illuminating System and Testing Notice
With the development of LED, LED lighting has been gradually developed to commercial stage for its advantage of non-pollution, long life, easy to transport, and other advantages. Because of uneven development of LED industry in China and some engineering staff is short of professional knowledge, which result in the LED lighting was used inappropriately and unreasonable and unqualified phenomenon of the LED lighting system. This paper was based on the principles and characteristics of LED lighting, discussed the LED lighting system design process and points for attention, combined with experience in engineering practice, and provided suggestions to resolve some related problems. We hope to help the engineering staff of LED lighting system design.
35950271
Partition Triangle Meshes into Coarsely Quadrangular Segmentation
A feature captured approach was presented to automatically partition a triangle meshes into a coarsely quadrangular segmentation. The triangle meshes was firstly partitioned into a polygonal segmentation which was further split into triangular and quadrangular patches. After the convex and concave features were identified, the triangular patches were eliminated according to their topological relations to achieve the quadrangular segmentation. The optimization methods based on globally smooth parameterization and active contour model were also adopted to improve the qualities of quadrangular patches and their edges. The final segmentation consisted of pure-quadrangular patches with appropriate sizes according to the model's geometric characteristics, and the features of input model werewell captured.
2208544
Personalized Modeling and Assessment of the Aortic-Mitral Coupling from 4D TEE and CT
The anatomy, function and hemodynamics of the aortic and mitral valves are known to be strongly interconnected. An integrated quantitative and visual assessment of the aortic-mitral coupling may have an impact on patient evaluation, planning and guidance of minimal invasive procedures. In this paper, we propose a novel model-driven method for functional and morphological characterization of the entire aortic-mitral apparatus. A holistic physiological model is hierarchically defined to represent the anatomy and motion of the two left heart valves. Robust learning-based algorithms are applied to estimate the patient-specific spatial-temporal parameters from four-dimensional TEE and CT data. The piecewise affine location of the valves is initially determined over the whole cardiac cycle using an incremental search performed in marginal spaces. Consequently, efficient spectrum detection in the trajectory space is applied to estimate the cyclic motion of the articulated model. Finally, the full personalized surface model of the aortic-mitral coupling is constructed using statistical shape models and local spatial-temporal refinement. Experiments performed on 65 4D TEE and 69 4D CT sequences demonstrated an average accuracy of 1.45 mm and speed of 60 seconds for the proposed approach. Initial clinical validation on model-based and expert measurement showed the precision to be in the range of the inter-user variability. To the best of our knowledge this is the first time a complete model of the aortic-mitral coupling estimated from TEE and CT data is proposed.
12791479
Group-by Query Process in Middleware of Large Scale Data Intensive Systems
Large scale data intensive systems are available in many fields in recent years, and it’s a severe challenge for group-by query of large volume of data in a cluster based on shared-nothing architecture. This paper proposes a design of a parallel query engine (PQE) and its asynchronous improvement (APQE) for group-by queries. PQE and APQE support for pipelined query processing and develop maximum degree of pipeline parallelism. APQE further eliminates the synchronous overhead of multi nodes parallelism, and returns part of final result as early as possible if no data dependency exists. Experimental results demonstrate that, compared to previous 2-step query engine, PQE and APQE can make a significant performance improvement for group-by query of large data sets in a shared-nothing cluster system, as well as obviously better scalability.
9823069
Multiple Tree Models for Occlusion and Spatial Constraints in Human Pose Estimation
Tree-structured models have been widely used for human pose estimation, in either 2D or 3D. While such models allow efficient learning and inference, they fail to capture additional dependencies between body parts, other than kinematic constraints between connected parts. In this paper, we consider the use of multiple tree models, rather than a single tree model for human pose estimation. Our model can alleviate the limitations of a single tree-structured model by combining information provided across different tree models. The parameters of each individual tree model are trained via standard learning algorithms in a single tree-structured model. Different tree models can be combined in a discriminative fashion by a boosting procedure. We present experimental results showing the improvement of our approaches on two different datasets. On the first dataset, we use our multiple tree framework for occlusion reasoning. On the second dataset, we combine multiple deformable trees for capturing spatial constraints between non-connected body parts.