Efficient Depth Map Estimation Method Based on Gradient Weight Cost Aggregation Strategy for Distributed Video Sensor Networks
Video sensor networking technologies have developed very rapidly in the last ten years. In this paper, a cross-based framework strategy for cost aggregation is presented for the depth map estimation based on video sensor networks. We formulate the process as a local regression problem consisting of...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/326029 |
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| _version_ | 1849397085014589440 |
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| author | Gwang-Soo Hong Byung-Gyu Kim Kee-Koo Kwon |
| author_facet | Gwang-Soo Hong Byung-Gyu Kim Kee-Koo Kwon |
| author_sort | Gwang-Soo Hong |
| collection | DOAJ |
| description | Video sensor networking technologies have developed very rapidly in the last ten years. In this paper, a cross-based framework strategy for cost aggregation is presented for the depth map estimation based on video sensor networks. We formulate the process as a local regression problem consisting of two main steps with a pair of video sensors. The first step is to calculate estimates for a set of points within a shape-adaptive local support region. The second step is to aggregate the matching cost for the gradient-based weight of the support region at the outmost pixel. The proposed algorithm achieves strong results in an efficient manner using the two main steps. We have achieved improvement of up to 6.9%, 8.4%, and 8.3%, when compared with adaptive support weight (ASW) algorithm. Comparing to cross-based algorithm, the proposed algorithm gives 2.0%, 1.3%, and 1.0% in terms of nonocclusion, all, and discontinuities, respectively. |
| format | Article |
| id | doaj-art-a8bfa15e4e834fce945e7ba870338224 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-a8bfa15e4e834fce945e7ba8703382242025-08-20T03:39:09ZengWileyInternational Journal of Distributed Sensor Networks1550-14772014-01-011010.1155/2014/326029326029Efficient Depth Map Estimation Method Based on Gradient Weight Cost Aggregation Strategy for Distributed Video Sensor NetworksGwang-Soo Hong0Byung-Gyu Kim1Kee-Koo Kwon2 Computer Engineering Department, SunMoon University, Republic of Korea Computer Engineering Department, SunMoon University, Republic of Korea Automotive IT Platform Research Team, ETRI, Republic of KoreaVideo sensor networking technologies have developed very rapidly in the last ten years. In this paper, a cross-based framework strategy for cost aggregation is presented for the depth map estimation based on video sensor networks. We formulate the process as a local regression problem consisting of two main steps with a pair of video sensors. The first step is to calculate estimates for a set of points within a shape-adaptive local support region. The second step is to aggregate the matching cost for the gradient-based weight of the support region at the outmost pixel. The proposed algorithm achieves strong results in an efficient manner using the two main steps. We have achieved improvement of up to 6.9%, 8.4%, and 8.3%, when compared with adaptive support weight (ASW) algorithm. Comparing to cross-based algorithm, the proposed algorithm gives 2.0%, 1.3%, and 1.0% in terms of nonocclusion, all, and discontinuities, respectively.https://doi.org/10.1155/2014/326029 |
| spellingShingle | Gwang-Soo Hong Byung-Gyu Kim Kee-Koo Kwon Efficient Depth Map Estimation Method Based on Gradient Weight Cost Aggregation Strategy for Distributed Video Sensor Networks International Journal of Distributed Sensor Networks |
| title | Efficient Depth Map Estimation Method Based on Gradient Weight Cost Aggregation Strategy for Distributed Video Sensor Networks |
| title_full | Efficient Depth Map Estimation Method Based on Gradient Weight Cost Aggregation Strategy for Distributed Video Sensor Networks |
| title_fullStr | Efficient Depth Map Estimation Method Based on Gradient Weight Cost Aggregation Strategy for Distributed Video Sensor Networks |
| title_full_unstemmed | Efficient Depth Map Estimation Method Based on Gradient Weight Cost Aggregation Strategy for Distributed Video Sensor Networks |
| title_short | Efficient Depth Map Estimation Method Based on Gradient Weight Cost Aggregation Strategy for Distributed Video Sensor Networks |
| title_sort | efficient depth map estimation method based on gradient weight cost aggregation strategy for distributed video sensor networks |
| url | https://doi.org/10.1155/2014/326029 |
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