Benchmark:

MOT17Det |

Short name:

ACF

Description:

The detector portion of this toolbox implements the Aggregate Channel
Features (ACF) object detection code. The ACF detector is a fast and
effective sliding window detector (30 fps on a single core). It is an
evolution of the Viola & Jones (VJ) detector but with an ~1000 fold
decrease in false positives (at the same detection rate). ACF is best
suited for quasi-rigid object detection (e.g. faces, pedestrians, cars).

The detection code was written by Piotr Dollar with contributions by Ron
Appel and Woonhyun Nam (with bug reports/suggestions from many others).

Reference:

P. Dollar, R. Appel, S. Belongie, P. Perona. Fast Feature Pyramids for Object Detection. In TPAMI, 2014.

Last submitted:

February 14, 2017 (7 years ago)

Published:

February 14, 2017 at 06:29:22 CET

Submissions:

4

Project page / code:

https://pdollar.github.io/toolbox/detector/acfReadme.html

Open source:

Yes

Hardware:

3GHz

Runtime:

74.0 Hz

Benchmark performance:

Detailed performance:

Raw data:

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