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We describe a method to select edgels and to calculate gradient orientation-based template descriptors for edgel features. An edgel is selected within a grid block based on gradient magnitude; its position and orientation are used to determine a canonical frame where the descriptor is computed based on quantized orientation. The resulting descriptor is efficiently matched using logical operations...
We propose a new technique to detect objects and collisions of geometric objects in cyber space. This technique uses depth values of the Z-buffer in rendering scene. We use the orthographic projection for collision detection. Our method uses two depth value sets. One is obtained through rendering the cyber space from the sensor object toward a target point. This set does not have the depth values...
We describe a method to select edgels and to calculate gradient orientation-based template descriptors for edgel features. An edgel is selected within a grid block based on gradient magnitude; its position and orientation are used to determine a canonical frame where the descriptor is computed based on quantized orientation. The resulting descriptor is efficiently matched using logical operations...
Effective robotic interaction with household objects requires the ability to recognize both object instances and object categories. The former are often characterized by locally discriminative texture cues (e.g., instances with prominent brand names and logos), and the latter by salient global shape properties (plates, bowls, pots). We describe experiments with both types of cues, combining a template-and-deformable-parts...
In this paper, we propose a graph-based shape matching method for deformable objects. In our approach, a graph is generated from an over-segmented input image, and the shape matching problem is treated as finding an optimal cycle in the graph. Given a shape template and a graph generated from the input, a product graph is generated to consider every possible correspondence between graph edges and...
Although the sketch recognition and computer vision communities attempt to solve similar problems in different domains, the sketch recognition community has not utilized many of the advancements made in computer vision algorithms. In this paper we propose using a pictorial structure model for object detection, and modify it to better perform in a drawing setting as opposed to photographs. By using...
We present an approach that directly uses curvature cues in a discriminative way to perform object recognition. We show that integrating curvature information substantially improves detection results over descriptors that solely rely upon histograms of orientated gradients (HoG). The proposed approach is generic in that it can be easily integrated into state-of-the-art object detection systems. Results...
Automatic target detection in satellite images remains a challenging problem. The main difficulties lie in the cooccurrence of variations of target type, pose, and size in huge satellite image. In this paper, we propose a new airplane detection approach based on visual saliency computation and symmetry detection. The advantages are twofold. First, saliency and symmetry detection perform stably in...
We address the problem of automatic color categorization of the objects in surveillance videos. This problem is challenging for realistic situations due to the large intra-class variations of the same color and the large portions of noisy areas including the backgrounds and the parts of the objects that do not contribute to color assignments. We develop an integrated color categorization system with...
In an effort to overcome the limitations of small target detection in complex urban scene, complementary data sets are combined to provide additional insight about a particular scene. This paper presents a method based on shape/spectral integration (SSI) decision level fusion algorithm to improve the detection of vehicles in semi and deep shadow areas. A four steps process combines high resolution...
We describe a new procedure that combines statistical and structural characteristics of simple primitive objects to discover compound structures in images. The statistical information that is modeled using spectral, shape, and position data of individual objects, and structural information that is modeled in terms of spatial alignments of neighboring object groups are encoded in a graph structure...
In order to detect the objects of interest, many different approaches have been proposed. One kind of popular approaches are based on template matching, which use a template of the object class to match the image at different positions. The matching can be computed using similarity measures such as the correlation coefficient. These approaches, although easy and robust, has the limitation of not containing...
This paper describes a framework for simultaneous identification and tracking of moving targets in random media. Video and IR thermal sensors are used to obtain the target signature. Classical Kalman filtering methods are implemented on targets with unknown trajectories. Computer vision methodologies are proposed to design a smart interceptor which identifies the targets based on shape and thermal...
The problem of amorphous object detection is investigated. A dataset of amorphous objects, Panda bears, with no defined shape or distinctive edge configurations is introduced. A biologically plausible amorphous object detector, based on discriminant saliency templates, is then proposed. The detector is based on the principles of discriminant saliency, and implemented with a hierarchical architecture...
This paper presents a new method to automatically detect occluded vehicle in semi or deep shadow areas using combined very high resolution (VHR) 3D LIDAR and hyperspectral data. The proposed shape/spectral integration (SSI) decision fusion algorithm was shown to outperform the spectral based anomaly algorithm mainly in deep shadow areas. The fusion of LIDAR DSM data with spectral data is useful in...
According to the features of the changing color of fire flames, the periodically increasing of area and the irregular changing in the shape of fire when the early fire breaks, we take fire flame as a kind of special moving object and make a research of it. The color characteristics in fire video images as well as the morphological changes are discussed in this paper, a comprehensive analysis of all...
In this paper, we describe a side-view car detection algorithm based on template detection. The template is constructed according to car shape knowledge. The algorithm can roughly be divided into two stages, hypothesis generation and hypothesis verification. In HG step, we use Hough transform to detect wheels, with the shape knowledge we get a rectangular area to generate hypothesis area. In HV step,...
We consider the problem of detecting targets behind walls using radar imaging technology. An image-domain based detection technique is proposed that allows to adapt to specific targets of interest. By doing so, clutter as well as targets of no-interest are strongly reduced in the radar image. The proposed detector is automatic in the sense that no or only little prior knowledge on the image statistics...
Combining advantages of shape and appearance features, we propose a novel model that integrates these two complementary features into a common framework for object categorization and detection. In particular, generic shape features are applied as a pre-filter that produces initial detection hypotheses following a weak spatial model, then the learnt class-specific discriminative appearance-based SVM...
In this paper we present a method to combine the detection and segmentation of object categories from 3D scenes. In the process, we combine the top-down cues available from object detection technique of Implicit Shape Models and the bottom-up power of Markov Random Fields for the purpose of segmentation. While such approaches have been tried for the 2D image problem domain before, this is the first...
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