Image recognition via deformable templates

Yen, Ester; Smith, A. F. M.

doi:10.1016/j.stamet.2005.05.001

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…Wu, 2009;Amira and Farrell, 2005). In the part-based approach (Ramanan and Sminchisescu, 2006;Ioffe and Forsyth, 2001;Kohandani et al, 2006;E. Yen, 2005;Lowe, 1991) an object is represented as a set of its parts, and it is represented as a graph with various parts connected by the edges of the graph.…”

Section: Introductionmentioning

confidence: 99%

Object Detection Using Pictorial Structure of Gabor Template

Saleh

Rastegari

2010

Proceedings of the International Conference on Computer Vision Theory and Applications

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Abstract:Object detection methods are divided into two main branches: In the global approach one extracts low level features and uses machine learning techniques. In the part-based approach one uses deformable templates. We present a Hybrid approach for constructing a deformable template for modeling and detection. Initially one applies Gabor wavelet filters to extract low level features and constructs graphs which resemble shock graphs. A minimum spanning tree (MST) is extracted and is called the pictorial graph. It is used for matching. The pictorial graph is suitable for preserving the visual appearance of the shape of the object and for accommodating shape variances. In this hybrid approach we maintain the generality of the global and the efficiency of part-based approaches. Our algorithm has been applied to a set of test cases and the result shows improved performance as compared to standard object detection methods that do not rely on human intervention.

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Section: Introductionmentioning

confidence: 99%

Object Detection Using Pictorial Structure of Gabor Template

Saleh

Rastegari

2010

Proceedings of the International Conference on Computer Vision Theory and Applications

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“…Such as algorithms on conventional template matching methods [1] [2], statistically feature methods [2] [3] and neutral network ways [4]. Wavelet transformation, and fractal theory has been used in object identify now.…”

Section: Introductionmentioning

confidence: 99%

A new strategy for object-identification based on its inherent geometrical characteristic

et al. 2007

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Object-identification using edge extraction techniques from background function in uncontrolled lighting environments containing more object pose information and have many applications. In order to depressing noise, identify aim body robustly and rapidly, in this paper, We take cuboid as model and present a new strategy for edge extraction and objectidentification based on object inherent features. This strategy includes the following steps. Firstly, pre-processing is applied to the raw image, in which Canny operator was used to extract edges pixels, then, image was divided into a grid of overlapping windows and noise was suppressed by regression grid windows in which the number of pixels is less than a threshold. Secondly, as model contour's geometry characters known already, the cuboids upright edges was used as their existence evidence to estimate model's existence area and so the lines failed spatial constraints are eliminated, then, object edges was extracted within the finite ranges of orientation in Hough transform space. Thirdly, the intersections of the component extracted edges are taken, the candidate edges extraction and matches was assessed based on the intersections, rather than the component extracted edges. After a series of matching tests the aim body is extracted. The proposed method makes three major contributions. Firstly, on the base of study the correspondence between model's boundary edges parameters in image space and Hough space we extract edges in finite area in Hough transform space, the aimless computations and searching is reduced greatly, its efficiency improved. Secondly, as Canny operator can extract aim lines with single pixel width, the edges extraction strategy of combining Canny operator with Hough transform extractor could avoid error impact of edges pixels numbers to Hough extractor. Thirdly, after fusion model's knowledge in image space, Hough space, global space, learning from others strong points to offset one's weakness, we extract model's edges from complex noise background without regarding to regression caused by the errors due to spurious or missing pixels because edge extraction is imperfect for real images. The results of experiments demonstrated that the proposed method could suppress noise effectively, identified and extracted target from complex backgrounds robustly. This new strategy may have potential application in visual servo, object tracking, port AGV and robots fields etc.

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Image recognition via deformable templates

Cited by 2 publications

References 9 publications

Object Detection Using Pictorial Structure of Gabor Template

Object Detection Using Pictorial Structure of Gabor Template

A new strategy for object-identification based on its inherent geometrical characteristic

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