Learning Social Affordance for Human-Robot Interaction
Authors: Tianmin Shu, M. S. Ryoo, Song-Chun Zhu
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The experimental results demonstrate that our Markov Chain Monte Carlo (MCMC) based learning algorithm automatically discovers semantically meaningful social affordance from RGB-D videos, which allows us to generate appropriate full body motion for an agent. |
| Researcher Affiliation | Academia | 1 Center for Vision, Cognition, Learning and Autonomy, University of California, Los Angeles 2 School of Informatics and Computing, Indiana University, Bloomington |
| Pseudocode | Yes | Algorithm 1 Learning Algorithm; Algorithm 2 Motion Synthesis Algorithm |
| Open Source Code | No | The paper states: 'The dataset is available at: http://www.stat.ucla.edu/ tianmin.shu/Social Affordance.' This link is for the dataset, not the open-source code for the methodology. There is no explicit statement about releasing the code for the described methods. |
| Open Datasets | Yes | We collected a new RGB-D video dataset, i.e., UCLA Human-Human-Object Interaction (HHOI) dataset, which includes 3 types of human-human interactions, i.e., shake hands, high-five, pull up, and 2 types of human-object-human interactions, i.e., throw and catch, and hand over a cup. On average, there are 23.6 instances per interaction performed by totally 8 actors recorded from various views. The dataset is available at: http://www.stat.ucla.edu/ tianmin.shu/Social Affordance. |
| Dataset Splits | Yes | We split the instances by four folds for the training and testing where the actor combinations in the testing set are different from the ones in the training set. |
| Hardware Specification | Yes | Our learning algorithm converges within 100 outer loop iterations, which takes 3-5 hours to run on a PC with an 8-core 3.6 GHz CPU. |
| Software Dependencies | No | The paper mentions 'Our motion synthesis can be ran at the average speed of 5 fps with our unoptimized Matlab code.' However, it does not provide a specific version number for Matlab or any other software dependencies. |
| Experiment Setup | Yes | In practice, we set λ = 1. β = 0.3 and γ = 1.0 are the parameters for our CRP. |