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Using feature selection for object segmentation and tracking

Using feature selection for object segmentation and tracking

引用

4th canadian conference on computer and robot vision

作者： Allili, Mohand Said Ziou, Djemel Univ Sherbrooke Dept Comp Sci Sherbrooke PQ J1K 2R1 Canada

ISBN: (纸本)9780769527864

Most image segmentation algorithms in the past are based on optimizing an objective function that aims to achieve the similarity between several low-level features to build a partition of the image into homogeneous regions. In the present paper we propose to incorporate the relevance (selection) of the grouping features to enforce the segmentation toward the capturing of objects of interest. The relevance of the features is determined through a set of positive and negative examples of a specific object defined a priori by the user The calculation of the relevance of the features is performed by maximizing an objective function defined on the mixture likelihoods of the positive and negative object examples sets. The incorporation of the features relevance in the object segmentation is formulated through an energy functional which is minimized by using level set active contours. We show the efficiency of the approach on several examples of object of interest segmentation and tracking where the features relevance was used.

关键词： segmentation object of interest (OOI) feature relevance positive & negative examples mixture model active contours

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Figure-ground segmentation using a hierarchical conditional random field

Figure-ground segmentation using a hierarchical conditional ...

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4th canadian conference on computer and robot vision

作者： Reynolds, Jordan Murphy, Kevin Univ British Columbia Vancouver BC V5Z 1M9 Canada

ISBN: (纸本)9780769527864

We propose an approach to the problem of detecting and segmenting generic object classes that combines three "off the shelf" components in a novel way. The components are a generic image segmenter that returns a set of "super pixels" at different scales;a generic classifier that can determine if an image region (such as one or more super pixels) contains (part of) the foreground object or not;and a generic belief propagation (BP) procedure for tree-structured graphical models. Our system combines the regions together into a hierarchical, tree-structured conditional random field, applies the classifier to each node (region), and fuses all the information together using belief propagation. Since our classifiers only rely on color and texture, they can handle deformable (non-rigid) objects such as animals, even under severe occlusion and rotation. We demonstrate good results for detecting and segmenting cows, cats and cars on the very challenging Pascal VOC dataset.

关键词： Image segmentation

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Learning saccadic gaze control via motion prediciton

Learning saccadic gaze control via motion prediciton

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4th canadian conference on computer and robot vision

作者： Forssen, Per-Erik Univ British Columbia Dept Comp Sci Vancouver BC V6T 1W5 Canada

ISBN: (纸本)9780769527864

This paper describes a system that autonomously learns to perform saccadic gaze control on a stereo pan-tilt unit. Instead of learning a direct map from image positions to a centering action, the system first learns a forward model that predicts how image features move in the visual field as the gaze is shifted. Gaze control can then be performed by searching for the action that best centers a feature in both the left and the right image. By attacking the problem in a different way we are able to collect many training examples in each action, and thus learning converges much faster The learning is performed using image features obtained from the Scale Invariant Feature Transform (SIFT) [14] detected and matched before and after a saccade, and thus requires no special environment during the training stage. We demonstrate that our system stabilises already after 300 saccades, which is more than 100 times fewer than the best current approaches.

关键词： Systems analysis

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SAR sea ice image segmentation based on edge-preserving watersheds

SAR sea ice image segmentation based on edge-preserving wate...

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4th canadian conference on computer and robot vision

作者： Yang, Xuezhi Clausi, David A. Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9780769527864

This paper presents a hybrid method for the segmentation of SAR sea ice images, which consists of an initial watershed segmentation followed by a region merging. Iterative bilateral filtering is used to reduce speckle noise and suppress irrelevant image details, which can significantly alleviate oversegmentation of watersheds. Since edges are well preserved by bilateral filtering, the watershed algorithm is capable of precisely locating object boundaries. Final segmentation is accomplished by applying an iterative region merging on the watershed regions by taking into account local boundary strengths and regional statistics. The efficiency of the proposed method has been demonstrated on the segmentation of SAR sea ice images. In comparison with traditional watershed algorithm, our method achieves better performance in identifying filament structures such as leads.

关键词： image segmentation synthetic aperture radar (SAR) sea ice bilateral filtering watershed

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Mapping and exploration of complex environments using persistent 3D model

Mapping and exploration of complex environments using persis...

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4th canadian conference on computer and robot vision

作者： Fournier, Jonathan Ricard, Benoit Laurendeau, Denis Univ Laval CVSL Quebec City PQ G1K 7P4 Canada Def R&D Canada Ottawa ON Canada

ISBN: (纸本)9780769527864

An increasingly popular approach to support military forces deployed in urban environments consists in using autonomous robots to carry on critical tasks such as mapping and surveillance. In order to cope with the complex obstacles and structures found it? this operational context, robots should be able to perceive and analyze their world in 3D. The method presented in this paper uses a 3D volumetric sensor to efficiency map and explore urban environments with an autonomous robotic platform. A key feature of our work is that the 3D model of the environment is preserved all along the process using a multiresolution octree. This way, every module can access the information it contains to achieve its tasks. Simulation and real word tests were performed to validate the performance of the integrated system and are presented at the end of the paper.

关键词： Military operations

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Automated detection of mitosis in embryonic tissues

Automated detection of mitosis in embryonic tissues

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4th canadian conference on computer and robot vision

作者： Siva, Parthipan Brodland, G. Wayne Clausi, David Univ Waterloo VIP Lab Waterloo ON N2L 3G1 Canada Univ Waterloo Embryo Biomech Grp Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9780769527864

Characterization of mitosis is important for understanding the mechanisms of development in early stage embryos. In studies of cancer another situation in which mitosis is of interest, the tissue is stained with contrast agents before mitosis characterization;an intervention that could lead to atypical development in live embryos. A new image processing algorithm that does not rely on the use of contrast agents was developed to detect mitosis in embryonic tissue. Unlike previous approaches that uses still images, the algorithm presented here uses temporal information from time-lapse images to track the deformation of the embryonic tissue and then. uses changes in intensity at tracked regions to identify the locations of mitosis. On a one hundred minute image sequence, consisting of twenty images, the algorithm successfully detected eighty-one out of the ninety-five mitosis. The performance of the algorithm is calculated using the geometric mean measure as 82%. Since no other method to count mitoses in live tissues is known, comparisons with the present results could not be made.

关键词： Tissue

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Super-resolution based on interpolation and global sub pixel translation

Super-resolution based on interpolation and global sub pixel...

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4th canadian conference on computer and robot vision

作者： Mecheri, Kamel Ziou, Djemel Deschenes, Francois Univ Sherbrooke Fac Sci Dept Informat Ctr Rech MOIVRE 2500 Blvd Univ Sherbrooke PQ J1K 2R1 Canada

ISBN: (纸本)9780769527864

In this paper we present a new class of reconstruction algorithms that are basically different from the traditional approaches. We deviate from the traditional technique which treats the pixels of the image as point samples. In this work, the pixels are treated as rectangular surface samples. It is in conformity with image formation process, in particular for CCD/CMOS sensors, which are a matrix of rectangular surfaces sensitive to the light. We show that results of better quality in terms of the measurements employed are obtained by formulating the reconstruction as a two-stage process: the restoration of image followed by the application of the point spread function (PSF) of the imaging sensor By coupling the PSF with the reconstruction process, we satisfy a measure of accuracy that is based on the physical limitations of the sensor. Effective techniques for the restoration of image are derived to invert the effects of the PSF and estimate the original image. For the algorithm of restoration, we introduce a new method of interpolation implying a sequence of images, not necessarily a temporal sequence, shifted compared to an image of reference.

关键词： super-resolution reconstruction intra-pixel restoration interpolation

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Spatial topology graphs for feature-minimal correspondence

Spatial topology graphs for feature-minimal correspondence

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4th canadian conference on computer and robot vision

作者： Tauber, Zinovi Li, Ze-Nian Drew, Mark S. Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada

ISBN: (纸本)9780769527864

Multiview image matching methods typically require feature point correspondences. We propose a novel spatial-topology method that represents the space with a set of connected projective invariant-features. Typically, isolated features, such as corners, cannot be matched reliably. Hence, limitations are imposed on viewpoint changes, or projective invariant descriptions are needed. The fundamental matrix is discovered using stochastic optimization requiring a large number of features. In contrast, our enhanced feature set models connectivity in space, forming a unique configuration that can be matched with few features and over large viewpoint changes. Our features are derived from edges, their curvatures, and neighborhood relationships. A probabilistic spatial topology graph models the space using these features and a second graph represents the neighborhood relationships. Probabilistic graph matching is used to find feature correspondences. Our results show robust feature detection and an average 80% discovery rate of feature matches.

关键词： Feature extraction

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Efficient indexing for strongly similar subimage retrieval

Efficient indexing for strongly similar subimage retrieval

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4th canadian conference on computer and robot vision

作者： Roth, Gerhard Scott, William Natl Res Council Canada Inst Informat Technol Montreal RdBldg M50 Ottawa ON K1A 0R6 Canada

ISBN: (纸本)9780769527864

strongly similar subimages contain different views of the same object. In subimage search, the user selects an image region and the retrieval system attempts to find matching subimages in an image database that are strongly similar Solutions have been proposed using salient features or '' interest points '' that have associated descriptor vectors. However, searching large image databases by exhaustive comparison of interest point descriptors is not feasible. To solve this problem, we propose a novel off-line indexing scheme based on the most significant bits (MSBs) of these descriptors. On-line search uses this index file to limit the search to interest points whose descriptors have the same MSB value, a process up to three orders of magnitude faster than exhaustive search. It is also incremental, since the index file for a union of a group of images can be created by merging the index files of the individual image groups. The effectiveness of the approach is demonstrated experimentally on a variety of image databases.

关键词： Image retrieval

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Robust subspace position measurement using localized sub-windows

Robust subspace position measurement using localized sub-win...

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4th canadian conference on computer and robot vision

作者： Smit, Aart Schuurman, Derek C. Redeemer Univ Coll Dept Comp Sci Ancaster ON L9K 1J4 Canada

ISBN: (纸本)9780769527864

The use of localized principal component analysis is examined for visual position determination in the presence of varying degrees of occlusions. Occlusions lead to substantial position measurement errors when projecting images into eigenspace. One way to improve robustness to occlusions is to select small sub-windows so that if some sub-windows are occluded, others can still accurately identify, position. The location of candidate sub-windows are predetermined from a set of training images by subtracting the average image from each and then selecting regions using an attention operator Since attention operators can be computationally time-intensive, the location of all sub-windows are determined a-priori during the training phase. The sub-windows in each of the training images are then projected into eigenspace. Once the training phase is complete, the run-time execution can be performed efficiently since all the sub-windows have been preselected. Input images are classified by each sub-window;majority voting is then used to determine the position estimate. Various experiments are performed including linear and rotational motion, and the ego motion of a mobile robot. This technique is shown to provide greater position measurement accuracy in the presence of severe occlusions as compared to the projection of entire images.

关键词： Position measurement

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