Bayesian Inference of Recursive Sequences of Group Activities from Tracks
Authors: Ernesto Brau, Colin Dawson, Alfredo Carrillo, David Sidi, Clayton Morrison
AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate the model s expressive power in several simulated and complex real-world scenarios from the VIRAT and UCLA Aerial Event video data sets. |
| Researcher Affiliation | Academia | 1Computer Science Department, Boston College; brauavil@bc.edu 2Department of Mathematics, Oberlin College; cdawson@oberlin.edu 3School of Information, University of Arizona; {isaac85,dsidi,claytonm}@email.arizona.edu |
| Pseudocode | No | The paper describes the MCMC sampling moves with explanatory text and diagrams (Figure 5), but does not provide formal pseudocode blocks. |
| Open Source Code | No | The paper does not provide any specific links or statements about the availability of open-source code for the described methodology. |
| Open Datasets | Yes | We evaluate the model on synthetic and real-world data; specifically on two publicly available group activity datasets, VIRAT (Oh et al. 2011) and the UCLA aerial event dataset (Shu et al. 2015). |
| Dataset Splits | No | The paper describes the datasets used for evaluation but does not specify explicit training/test/validation dataset splits needed for reproducibility (e.g., percentages or sample counts for each split). |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., GPU models, CPU types) used for running the experiments. |
| Software Dependencies | No | The paper mentions 'DBSCAN' and 'hidden Markov model' but does not provide specific version numbers for any software dependencies. |
| Experiment Setup | No | The paper describes the MCMC sampling framework and proposal mechanisms but does not provide concrete hyperparameter values or detailed system-level training settings for their experiments. |