Low power architecture for fall detection system Thi Khanh Hong Nguyen To cite this version: Thi Khanh Hong Nguyen. Low power architecture for fall detection system. Other. Université Nice Sophia Antipolis, 2015. English. NNT : 2015NICE4093. tel-01288526 HAL Id: tel-01288526 https://tel.archives-ouvertes.fr/tel-01288526 Submitted on 15 Mar 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. UNIVERSITE NICE-SOPHIA ANTIPOLIS ECOLE DOCTORALE STIC SCIENCES ET TECHNOLOGIES DE L’INFORMATION ET DE LA COMMUNICATION T H E S E pour obtenir le titre de Docteur en science De l’Université Nice-Sophia Antipolis Mention: Présentée et soutenue par Thi Khanh Hong NGUYEN Low power architecture for Fall Detection System Thèse dirigée par Cecile BELLEUDY et Van Tuan PHAM Soutenue le 18 Novembre 2015 Jury: Mme. Nathalie Julien Professeur à l’Université Rapporteur de Bretagne Sud M. Bertrand Granado Professeur à l’Université de Rapporteur Pierre and Marie Curie Mme. Cecile BELLEUDY Maitre de Conférences, HDR, Directrice Université Nice Sophia Antipolis M. Van Tuan PHAM Associate Professeur, Co-directeur Université de Science et Technologie, Université de Da Nang. M. François Brémond Directeur de recherche de INRIA Examinateur i Contents Abstract ...................................................................................................................................... ix Résumé ...................................................................................................................................... xi Acknowledgement ................................................................................................................... xiii Chapter 1. Introduction ........................................................................................................ 1 1.1 The healthcare systems ......................................................................................................... 2 1.1.1 The healthcare system based on sensors ................................................................ 2 1.1.2 The healthcare system based on audio ................................................................... 4 1.1.3 The healthcare system based on communication network .................................... 4 1.1.4 The healthcare system based on intelligent video surveillance ............................. 5 1.2 Fall Detection Approaches. .................................................................................................. 6 1.2.1 Classification Fall Detection Approach ................................................................. 6 1.2.2 Efficient Architecture for Fall Detection on heterogeneous platform ................... 8 1.3 Research questions ............................................................................................................. 11 1.4 Thesis contributions ............................................................................................................ 12 1.5 Publications ........................................................................................................................ 14 1.5.1 International journal publication .......................................................................... 14 1.5.2 International conference’s publication................................................................. 14 1.5.3 Other publications ................................................................................................ 15 1.6 Thesis Organization ............................................................................................................ 15 Chapter 2. Fall Detection Algorithm .................................................................................. 17 2.1 Overview of Fall Detection algorithm ................................................................................ 17 2.1.1 Definition of falling event ................................................................................... 17 2.1.2 Fall Detection algorithms .................................................................................... 18 2.2 Proposed Fall Detection Algorithm .................................................................................... 22 2.2.1 Object Segmentation ............................................................................................ 23 2.2.2 Object Enhancement ............................................................................................ 25 2.2.3 Object Feature Extraction .................................................................................... 28 2.3 Recognition event ............................................................................................................... 36 2.3.1 Threshold-based algorithm .................................................................................. 36 ii 2.3.2 Neural Network algorithm ................................................................................... 37 2.3.3 Hidden Markov Model algorithm. ....................................................................... 39 2.4 Evaluation ........................................................................................................................... 40 2.4.1 DUT-HBU database ............................................................................................. 40 2.4.2 Performance measurement ................................................................................... 44 2.4.3 Performance of the system based on Hidden Markov Model .............................. 51 2.4.5 Analysis of error recognition ............................................................................... 54 2.5 General discussion .............................................................................................................. 57 2.5.1 Performance under real-life conditions ............................................................... 58 2.5.2 Usability ............................................................................................................... 58 2.6 Conclusion .......................................................................................................................... 58 Chapter 3. Power and Time Model Methodology for Fall Detection System ................... 61 3.1 Power and energy consumption characterization and estimation in MPSoC ..................... 62 3.2 Power consumption modeling approaches ......................................................................... 63 3.2.1 Low-level power consumption estimation techniques......................................... 63 3.2.2 High-level power consumption estimation techniques ........................................ 67 3.3 Execution time estimation approaches ............................................................................... 73 3.3.1 Static timing estimation ....................................................................................... 73 3.3.2 Dynamic timing estimation .................................................................................. 74 3.3.3 Timing estimation tools ....................................................................................... 75 3.4 Heterogeneous platform: Zynq7000 AP SoC platform ...................................................... 77 3.4.1 Motivation ............................................................................................................ 77 3.4.2 Description of Zynq-7000 AP SoC ...................................................................... 78 3.4.3 The Performance Monitor Unit (PMU) ............................................................... 79 3.5 Power/execution time models for video applications ......................................................... 81 3.5.1 Power estimation methodology for Fall Detection System ................................. 81 3.5.2 Power measurement ............................................................................................. 83 3.5.3 Execution time measurement ............................................................................... 85 3.6 Proposed power model of the Fall Detection System on heterogeneous platform ............. 86 3.6.1 Power models for processor ................................................................................. 86 3.6.2 Power models for hardware ................................................................................. 95 3.6.3 Power consumption models for heterogeneous architecture ............................... 97 iii 3.7 Execution time models for heterogeneous platform ........................................................... 97 3.7.1 Execution time models for processor .................................................................. 98 3.7.2 Times models for hardware acceleration (FPGA) ............................................. 100 3.8 Conclusion ........................................................................................................................ 101 Chapter 4. Low Cost Architecture for Fall Detection System ......................................... 103 4.1 High