Caltech Pedestrian Detection Benchmark
2D Box
Autonomous Driving
License: Unknown


The Caltech Pedestrian Dataset consists of approximately 10 hours of 640x480 30Hz video taken from a vehicle driving through regular traffic in an urban environment. About 250, 000 frames (in 137 approximately minute long segments) with a total of 350,000 bounding boxes and 2300 unique pedestrians were annotated.

Data Annotation

The annotation includes temporal correspondence between bounding boxes and detailed occlusion labels. More information can be found in our PAMI 2012 and CVPR 2009 benchmarking papers.

Data Format

The training data (set00-set05) consists of six training sets (~1GB each), each with 6-13 one-minute long seq files, along with all annotation information (see the paper for details). The testing data (set06-set10) consists of five sets, again ~1GB each.

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