Multiple camera-based chamfer matching for pedestrian detection

Katz, Itai; Aghajan, Hamid

doi:10.1109/icdsc.2008.4635734

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Figure 2 -Results Of Distance Transform1

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Cited by 5 publications

(3 citation statements)

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“…Chamfer matching is a special case of template matching [29]. The template F is shifted over an edge-mapped image DT and for each position the distance metric D Chamfer is computed, which is defined as…”

Section: Figure 2 -Results Of Distance Transformmentioning

confidence: 99%

Body Parts Features-Based Pedestrian Detection for Active Pedestrian Protection System

Guo

Zhang

et al. 2016

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Section: Figure 2 -Results Of Distance Transformmentioning

confidence: 99%

Body Parts Features-Based Pedestrian Detection for Active Pedestrian Protection System

Guo

Zhang

et al. 2016

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“…For edge based shape matching, Chamfer distance [3], [18], [13] and Hausdorff distance [12], [17] are two typically used criteria to compare images. The advantages lie in efficient computations made by the use of distance transforms (DT).…”

Section: Related Workmentioning

confidence: 99%

Shape Matching by Region Grouping

Gao

Yau

2010

2010 Fourth Pacific-Rim Symposium on Image and Video Technology

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In this paper, we propose a novel region grouping approach to shape matching. It is proposed as an alternative region based approach to the traditional edge based shape matching using distance transforms. It has the advantage of obtaining a higher detection rate and obtaining meaningful object segmentation simultaneously. Each image is first segmented into image regions, and possible matches are found among the regions based on a proposed probabilistic similarity measure to the exemplars. We evaluate this new approach against edge based matching using Chamfer and Hausdorff distances. Pros and cons of the proposed method are discussed.

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“…For edge based shape matching, Chamfer distance [16,153,134,73] and Hausdorff distance [70,103,131] are two typically used criteria to compare images. The advantages lie in efficient computations made by the use of distance transforms (DT).…”

Section: Related Workmentioning

confidence: 99%

Gaussian processes for pattern recognition applications

Gao¹

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Multiple camera-based chamfer matching for pedestrian detection

Cited by 5 publications

References 12 publications

Body Parts Features-Based Pedestrian Detection for Active Pedestrian Protection System

Body Parts Features-Based Pedestrian Detection for Active Pedestrian Protection System

Shape Matching by Region Grouping

Gaussian processes for pattern recognition applications

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