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Showing 1 to 15 of 15 for “"motion segmentation"”.

  1. Edge-based motion segmentation

    Motion segmentation is the process of dividing video frames into regions which have different motions, providing a cut-out of the moving objects. Such a segmentation is a necessary first stage in many video analysis applications, but providing an accurate, efficient motion segmentation still …

    cambridge Repository record for Edge-based motion segmentation (opens in a new tab)

  2. Robust motion segmentation using Markov thresholds

    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.

    mit Repository record for Robust motion segmentation using Markov thresholds (opens in a new tab)

  3. Learning static object segmentation from motion segmentation

    This thesis describes the SANE (Segmentation According to Natural Examples) algorithm for learning to segment objects in static images from video data. SANE uses background subtraction to find the segmentation of moving objects in videos. This provides object segmentation information for each video …

    mit Repository record for Learning static object segmentation from motion segmentation (opens in a new tab)

  4. Speeding up Adaboost object detection with motion segmentation and Haar feature acceleration

    … an object detection system that uses object segmentation as a preprocessing step. We use Mixture of Gaussians (MoG) proposed by Staffer et. al. for object segmentation. One key advantage with using segmentation to extract image regions of interest is that it reduces the number of search …

    dcu Repository record for Speeding up Adaboost object detection with motion segmentation and Haar feature acceleration (opens in a new tab)

  5. Segmentation in image sequences : tracking human figures in motion

    This thesis addressed the issue of segmentation and tracking of human figures in video sequences. Various issues affecting segmentation are investigated, including selection of a colour space representation. Different methods for segmentation are implemented and their respsective merits and …

    cape-town Repository record for Segmentation in image sequences : tracking human figures in motion (opens in a new tab)

  6. Learning articulated motions from visual demonstration

    … kinematic linkages purely by observing its motion during manipulation. This work proposes a framework that enables robots to learn the articulation in objects from user-provided demonstrations, using RGB-D sensors. We introduce algorithms that combine concepts in sparse feature tracking, …

    mit Repository record for Learning articulated motions from visual demonstration (opens in a new tab)

  7. Geometric Principles of Multiple Visual Sensors

    … approach for studying the structure-from-motion problem, which is a set of rank conditions on the multiple-view matrices of image features. This approach can be applied to characterize the algebraic conditions governing the multiple views of any type of image features and any kind of …

    uiuc Repository record for Geometric Principles of Multiple Visual Sensors (opens in a new tab)

  8. Fusion of Frequency and Spatial Domain Information for Motion Analysis

    … new approaches for the analysis of multiple motions in video, which integrates frequency and spatial-domain information. The tasks of interest are finding the number of moving objects, velocity estimation, object tracking, and motion segmentation. The proposed hybrid approach performs the …

    uiuc Repository record for Fusion of Frequency and Spatial Domain Information for Motion Analysis (opens in a new tab)

  9. MULTIPLE STRUCTURE RECOVERY VIA PREFERENCE ANALYSIS IN CONCEPTUAL SPACE

    … side, preference analysis concentrates on the segmentation side in order to find a proper partition of the data, from which model estimation follows. The research conducted in this thesis attempts to provide theoretical footing to the preference approach and to elaborate it in term of …

    milano Repository record for MULTIPLE STRUCTURE RECOVERY VIA PREFERENCE ANALYSIS IN CONCEPTUAL SPACE (opens in a new tab)

  10. Intelligent video surveillance

    … of parameters. The approach is based on rigid motion segmentation by Bayesian filtering. The Bayesian filter, which was proposed specially for this method and contributes to its novelty, is formulated as a generic approach, and then applied to the video analytics problems. The method is …

    lancaster Repository record for Intelligent video surveillance (opens in a new tab)

  11. Computational Modeling Approaches For Task Analysis In Robotic-Assisted Surgery

    … robotic surgery systems to record quantitative motion and video data motivates developing descriptive mathematical models to recognize, classify and analyze surgical tasks. Recent advances in machine learning research for uncovering concealed patterns in huge data sets, like kinematic and video …

    wayne-thes Repository record for Computational Modeling Approaches For Task Analysis In Robotic-Assisted Surgery (opens in a new tab)

  12. Depth map recovery from videos

    The depth map of a video is a very important piece of information. Recovering the depth map of a video expands a 2D video into its 3rd dimension, and creates new possibilities, such as, object insertion, conversion to 3D, shallow depth of field simulation. In this work, we introduce our approach of …

    uiuc Repository record for Depth map recovery from videos (opens in a new tab)

  13. Image Segmentation and Range Estimation Using a Moving-aperture Lens

    … to group the image points into logical objects (segmentation) and to determine the locations in the scene (range estimation). Despite the decades of research, a single solution is yet to be found. Through our research we have demonstrated that a possible solution is to use moving aperture lens. …

    vt Repository record for Image Segmentation and Range Estimation Using a Moving-aperture Lens (opens in a new tab)

  14. Image Based View Synthesis

    … and accurately segment the scene into several motion layers. First, a number of seed regions using correspondences in two frames are determined, and the seed regions are expanded and outliers are rejected employing the graph cuts method integrated with level set representation. Next, these …

    ucf