RGB-Depth Image Based Human Detection Using Viola-Jones and Chan-Vese Active Contour Segmentation

Lestari, Puji; Schade, Hans-Peter

doi:10.1007/978-3-319-67934-1_25

Cited by 2 publications

(1 citation statement)

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“…Almost all types of cameras have been proposed and evaluated for the human detection accuracy enhancement. The most widespread video devices are visual cameras, generating grayscale or RGB images [9] [10]. Some drawbacks related to the utilization of such devices under several conditions are: the objects' visibility which depends on energy sources (e.g.…”

Section: Introductionmentioning

confidence: 99%

Vision and Geolocation Data Combination for Precise Human Detection and Tracking in Search and Rescue Operations

Lygouras¹

2020

IJIS

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In this paper, a study and evaluation of the combination of GPS/GNSS techniques and advanced image processing algorithms for distressed human detection, positioning and tracking, from a fully autonomous Unmanned Aerial Vehicle (UAV)-based rescue support system, are presented. In particular, the issue of human detection both on terrestrial and marine environment under several illumination and background conditions, as the human silhouette in water differs significantly from a terrestrial one, is addressed. A robust approach, including an adaptive distressed human detection algorithm running every N input image frames combined with a much faster tracking algorithm, is proposed. Real time or near-real-time distressed human detection rates achieved, using a single, low cost day/night NIR camera mounted onboard a fully autonomous UAV for Search and Rescue (SAR) operations. Moreover, the generation of our own dataset, for the image processing algorithms training is also presented. Details about both hardware and software configuration as well as the assessment of the proposed approach performance are fully discussed. Last, a comparison of the proposed approach to other human detection methods used in the literature is presented.

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Section: Introductionmentioning

confidence: 99%

Vision and Geolocation Data Combination for Precise Human Detection and Tracking in Search and Rescue Operations

Lygouras¹

2020

IJIS

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Efficient Human Detection Algorithm using Color & Depth information with Accurate Outer Boundary Matching

Lestari

Schade

2019

2019 International Conference on Computer, Control, Informatics and Its Applications (IC3INA)

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RGB-Depth Image Based Human Detection Using Viola-Jones and Chan-Vese Active Contour Segmentation

Cited by 2 publications

References 32 publications

Vision and Geolocation Data Combination for Precise Human Detection and Tracking in Search and Rescue Operations

Vision and Geolocation Data Combination for Precise Human Detection and Tracking in Search and Rescue Operations

Efficient Human Detection Algorithm using Color & Depth information with Accurate Outer Boundary Matching

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