Publication detail

EnMS: Early non-Maxima Suppression

HEROUT, A. HRADIŠ, M. ZEMČÍK, P.

Original Title

EnMS: Early non-Maxima Suppression

Type

journal article - other

Language

English

Original Abstract

Detection of objects in images using statistical classifiers is a well studied and documented technique.  Different applications of such detectors often require selection of the image position with the highest response of the detector -- they perform non-maxima suppression.  This article introduces the concept of Early non-Maxima Suppression, which aims to reduce necessary computations by making the non-Maxima Suppression decision early based on incomplete information provided by a partially evaluated classifier. We show that the error of one such speculative decision with respect to a decision made based on response of the complete classifier can be estimated by collecting statistics on unlabeled data.  The article then considers a sequential strategy of multiple early non-Maxima suppression tests which follows the structure of soft-cascade detectors commonly used for object detection. We also show that an optimal (fastest for requested error rate) suppression strategy can be created by a novel variant of Wald's sequential probability ratio test (SPRT) which we call the Conditioned SPRT, CSPRT.  Experimental results show that the Early non-Maxima Suppression significantly reduces amount of computation in the case of object localization while the error rates are limited to low predefined values. The proposed approach notably outperforms the state-of-the-art detectors based on WaldBoost. The potential applications of the early non-Maxima suppression approach are not limited to object localization and could be applied wherever the goal is to find the strongest response of a classifier among a set of classified samples.

Keywords

Non-Maxima Suppression, Object Detection, WaldBoost, Sequential Probability Ratio Test

Authors

HEROUT, A.; HRADIŠ, M.; ZEMČÍK, P.

RIV year

2012

Released

1. 5. 2012

ISBN

1433-7541

Periodical

PATTERN ANALYSIS AND APPLICATIONS

Year of study

2012

Number

2

State

United Kingdom of Great Britain and Northern Ireland

Pages from

121

Pages to

132

Pages count

12

BibTex

@article{BUT76262,
  author="Adam {Herout} and Michal {Hradiš} and Pavel {Zemčík}",
  title="EnMS: Early non-Maxima Suppression",
  journal="PATTERN ANALYSIS AND APPLICATIONS",
  year="2012",
  volume="2012",
  number="2",
  pages="121--132",
  issn="1433-7541"
}