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Procedure Step Recognition

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 0
평가표: 1
보존된 평가 기록: 2

Procedure Step Recognition (PSR) focuses on recognizing the correct completion and order of procedural steps. Unlike traditional action recognition, which lacks a measure of success for actions, PSR aims to provide a meaningful understanding for procedural videos: recognizing the outcome (complete? correct?) of a procedural step is often more relevant than recognizing (partial) execution of an action.

Therefore, the objective of PSR is to extract an estimate of all procedure steps correctly performed by a person up to time $t$, based on sensory inputs $X_t=(x_t, x_{t-1}, \dots, x_{t-h})$ and a descriptive set of the procedural actions to be performed $\mathcal{P}=\{a_0, a_1, \dots, a_n\}$. Here, $h$ is the observation horizon and $n+1$ the total number of actions~$a_i\in \mathcal{P}$ covered in the procedure.

데이터셋

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IndustReal

IndustReal is an ego-centric, multi-modal dataset where 27 participants are challenged to perform assembly and maintenance procedures on a construction-toy car. The dataset is annotated for action recognition, assembly state detection, and procedure step recognition. IndustReal includes 38 execution errors in a total of 84 videos, with 14 exclusive to validation and test sets and therefore suitable for testing the robustness of algorithms against unseen errors in procedural tasks. IndustReal offers open-source 3D models for all parts to promote the use of synthetic data for scalable approaches on this dataset, as well as reproducibility. All assembly parts used in the dataset are 3D printed. This ensures reproducibility and future availability of the model and allows for growth via community effort. IndustReal can be used to test methods towards (video) procedure understanding, industrial automation, and to quantify performance of augmented reality applications.

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