Bird-Count: a multi-modality benchmark and system for bird population counting in the wild
The fluctuation of the bird population reflects the change in the ecosystem, which plays a vital role in ecosystem conservation. However, manual counting is still the mainstream method for bird population counting, which is time-consuming and laborious. One major bottleneck in developing efficient,...
| Main Authors: | , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer US
2023
|
| Online Access: | https://hdl.handle.net/1721.1/153063 |
| _version_ | 1811094736224649216 |
|---|---|
| author | Wang, Hongchang Lu, Huaxiang Guo, Huimin Jian, Haifang Gan, Chuang Liu, Wu |
| author2 | MIT-IBM Watson AI Lab |
| author_facet | MIT-IBM Watson AI Lab Wang, Hongchang Lu, Huaxiang Guo, Huimin Jian, Haifang Gan, Chuang Liu, Wu |
| author_sort | Wang, Hongchang |
| collection | MIT |
| description | The fluctuation of the bird population reflects the change in the ecosystem, which plays a vital role in ecosystem conservation. However, manual counting is still the mainstream method for bird population counting, which is time-consuming and laborious. One major bottleneck in developing efficient, accurate, and intelligent learning algorithms to counting birds is the lack of large-scale datasets. In this paper, the first large-scale bird population counting dataset, named Bird-Count, with multi-modality morphology annotations is proposed. This paper first evaluates various state-of-the-art (SOTA) models for crowd counting on the Bird-Count and gets poor results. The reason is that the forms, appearances, and postures among different birds are more variant than the crowd. To mitigate these challenges, a simple yet effective plug-and-play framework, called Morphology Prior Knowledge Fusion Network (MPKNet), which can be used on-site to help generate a high-precision bird population density map by incorporating morphological prior knowledge, is proposed. Comprehensive evaluations show that the proposed method can reduce the error rate by 6.02% compared with the current SOTA crowd counting algorithms on average. Moreover, with the above technologies, the intelligent bird population monitoring system is deployed in several important wetland national nature reserves for bird protection. |
| first_indexed | 2024-09-23T16:04:16Z |
| format | Article |
| id | mit-1721.1/153063 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T16:04:16Z |
| publishDate | 2023 |
| publisher | Springer US |
| record_format | dspace |
| spelling | mit-1721.1/1530632024-09-16T04:48:44Z Bird-Count: a multi-modality benchmark and system for bird population counting in the wild Wang, Hongchang Lu, Huaxiang Guo, Huimin Jian, Haifang Gan, Chuang Liu, Wu MIT-IBM Watson AI Lab The fluctuation of the bird population reflects the change in the ecosystem, which plays a vital role in ecosystem conservation. However, manual counting is still the mainstream method for bird population counting, which is time-consuming and laborious. One major bottleneck in developing efficient, accurate, and intelligent learning algorithms to counting birds is the lack of large-scale datasets. In this paper, the first large-scale bird population counting dataset, named Bird-Count, with multi-modality morphology annotations is proposed. This paper first evaluates various state-of-the-art (SOTA) models for crowd counting on the Bird-Count and gets poor results. The reason is that the forms, appearances, and postures among different birds are more variant than the crowd. To mitigate these challenges, a simple yet effective plug-and-play framework, called Morphology Prior Knowledge Fusion Network (MPKNet), which can be used on-site to help generate a high-precision bird population density map by incorporating morphological prior knowledge, is proposed. Comprehensive evaluations show that the proposed method can reduce the error rate by 6.02% compared with the current SOTA crowd counting algorithms on average. Moreover, with the above technologies, the intelligent bird population monitoring system is deployed in several important wetland national nature reserves for bird protection. 2023-11-29T14:38:16Z 2023-11-29T14:38:16Z 2023-04-29 2023-11-29T04:24:37Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/153063 Wang, Hongchang, Lu, Huaxiang, Guo, Huimin, Jian, Haifang, Gan, Chuang et al. 2023. "Bird-Count: a multi-modality benchmark and system for bird population counting in the wild." en https://doi.org/10.1007/s11042-023-14833-z Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature application/pdf Springer US Springer US |
| spellingShingle | Wang, Hongchang Lu, Huaxiang Guo, Huimin Jian, Haifang Gan, Chuang Liu, Wu Bird-Count: a multi-modality benchmark and system for bird population counting in the wild |
| title | Bird-Count: a multi-modality benchmark and system for bird population counting in the wild |
| title_full | Bird-Count: a multi-modality benchmark and system for bird population counting in the wild |
| title_fullStr | Bird-Count: a multi-modality benchmark and system for bird population counting in the wild |
| title_full_unstemmed | Bird-Count: a multi-modality benchmark and system for bird population counting in the wild |
| title_short | Bird-Count: a multi-modality benchmark and system for bird population counting in the wild |
| title_sort | bird count a multi modality benchmark and system for bird population counting in the wild |
| url | https://hdl.handle.net/1721.1/153063 |
| work_keys_str_mv | AT wanghongchang birdcountamultimodalitybenchmarkandsystemforbirdpopulationcountinginthewild AT luhuaxiang birdcountamultimodalitybenchmarkandsystemforbirdpopulationcountinginthewild AT guohuimin birdcountamultimodalitybenchmarkandsystemforbirdpopulationcountinginthewild AT jianhaifang birdcountamultimodalitybenchmarkandsystemforbirdpopulationcountinginthewild AT ganchuang birdcountamultimodalitybenchmarkandsystemforbirdpopulationcountinginthewild AT liuwu birdcountamultimodalitybenchmarkandsystemforbirdpopulationcountinginthewild |