gait recognition by gait energy image

code running environment

language version: python 3.5 os system: Linux or Unix, test on OS X 10.11.5

python library dependency

• scikit-learn==0.17.1

algorithm pipeline

do normalization and horizontal alignment to extracted silhouette sequences which are provided from CASIA Dataset B, more detail from the paper *(2005PAMI)The HumanID Gait Challenge Problem_Data Sets, Performance, and Analysis*

how to run

Before running the project, ensure you have:

1. Downloaded & extracted the silhouette sequences from the CASIA-B dataset.
2. Cloned or forked this repository and have all necessary dependencies installed as per above data.

Follow these step-by-step instructions to configure and execute the pipeline:

1. Configure the Dataset Path

Open the config.py file in your project directory and update the casia_dataset_b_path variable to point to the absolute path of your extracted CASIA-B silhouette sequences:

# config.py
casia_dataset_b_path = "/path/to/your/extracted/CASIA-B/silhouettes"

2. Run the Main Script

Execute the primary pipeline script from your terminal. Ensure your terminal is navigated to the root directory of the project:

python main.py

3. Monitor Execution Logs

The pipeline writes detailed runtime metrics and progress to a log file. To monitor this in real-time, open a terminal window and run:

tail -f main.py.log

method detail

read more from paper *Individual Recognition Using Gait Energy Image*