動物線索:通過痕跡識別動物
AnimalClue: Recognizing Animals by their Traces
July 27, 2025
作者: Risa Shinoda, Nakamasa Inoue, Iro Laina, Christian Rupprecht, Hirokatsu Kataoka
cs.AI
摘要
野生動物觀測在生物多樣性保護中扮演著重要角色,這要求我們採用穩健的方法來監測野生動物種群及其種間互動。近年來,計算機視覺的進步顯著推動了野生動物觀測基礎任務的自動化,如動物檢測和物種識別。然而,從足跡和糞便等間接證據中準確識別物種的研究相對不足,儘管這對野生動物監測至關重要。為彌補這一空白,我們推出了AnimalClue,這是首個基於間接證據圖像進行物種識別的大規模數據集。該數據集包含159,605個邊界框,涵蓋五類間接線索:足跡、糞便、卵、骨骼和羽毛,涉及968個物種、200個科和65個目。每張圖像均標註有物種級別標籤、邊界框或分割掩碼,以及細粒度特徵信息,如活動模式和棲息地偏好。與現有主要關注直接視覺特徵(如動物外觀)的數據集不同,AnimalClue因需識別更為細微和隱蔽的視覺特徵,為分類、檢測和實例分割任務帶來了獨特挑戰。在實驗中,我們廣泛評估了代表性視覺模型,並從動物痕跡識別中發現了關鍵挑戰。我們的數據集和代碼可在https://dahlian00.github.io/AnimalCluePage/獲取。
English
Wildlife observation plays an important role in biodiversity conservation,
necessitating robust methodologies for monitoring wildlife populations and
interspecies interactions. Recent advances in computer vision have
significantly contributed to automating fundamental wildlife observation tasks,
such as animal detection and species identification. However, accurately
identifying species from indirect evidence like footprints and feces remains
relatively underexplored, despite its importance in contributing to wildlife
monitoring. To bridge this gap, we introduce AnimalClue, the first large-scale
dataset for species identification from images of indirect evidence. Our
dataset consists of 159,605 bounding boxes encompassing five categories of
indirect clues: footprints, feces, eggs, bones, and feathers. It covers 968
species, 200 families, and 65 orders. Each image is annotated with
species-level labels, bounding boxes or segmentation masks, and fine-grained
trait information, including activity patterns and habitat preferences. Unlike
existing datasets primarily focused on direct visual features (e.g., animal
appearances), AnimalClue presents unique challenges for classification,
detection, and instance segmentation tasks due to the need for recognizing more
detailed and subtle visual features. In our experiments, we extensively
evaluate representative vision models and identify key challenges in animal
identification from their traces. Our dataset and code are available at
https://dahlian00.github.io/AnimalCluePage/