An optimization based framework for human pose estimation in monocular videos

Priyanshu Agarwal, Suren Kumar, Julian Ryde, Jason J. Corso, Venkat N. Krovi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Human pose estimation using monocular vision is a challenging problem in computer vision. Past work has focused on developing efficient inference algorithms and probabilistic prior models based on captured kinematic/dynamic measurements. However, such algorithms face challenges in generalization beyond the learned dataset. In this work, we propose a model-based generative approach for estimating the human pose solely from uncalibrated monocular video in unconstrained environments without any prior learning on motion capture/image annotation data. We propose a novel Product of Heading Experts (PoHE) based generalized heading estimation framework by probabilistically-merging heading outputs (probabilistic/ non-probabilistic) from time varying number of estimators to bootstrap a synergistically integrated probabilistic-deterministic sequential optimization framework for robustly estimating human pose. Novel pixel-distance based performance measures are developed to penalize false human detections and ensure identity-maintained human tracking. We tested our framework with varied inputs (silhouette and bounding boxes) to evaluate, compare and benchmark it against ground-truth data (collected using our human annotation tool) for 52 video vignettes in the publicly available DARPA Mind's Eye Year I dataset. Results show robust pose estimates on this challenging dataset of highly diverse activities.

Original languageEnglish
Title of host publicationAdvances in Visual Computing - 8th International Symposium, ISVC 2012, Revised Selected Papers
Pages575-586
Number of pages12
EditionPART 1
DOIs
StatePublished - 2012
Event8th International Symposium on Visual Computing, ISVC 2012 - Rethymnon, Crete, Greece
Duration: 16 Jul 201218 Jul 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7431 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Symposium on Visual Computing, ISVC 2012
Country/TerritoryGreece
CityRethymnon, Crete
Period16/07/1218/07/12

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