Human Detection and Identification by Robots Using Thermal and Visual Information in Domestic Environments

Correa, Mauricio; Hermosilla, Gabriel; Verschae, Rodrigo; Ruiz‐del‐Solar, Javier

doi:10.1007/s10846-011-9612-2

Cited by 51 publications

(30 citation statements)

References 35 publications

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“…As a result, an attractive solution is the combination of both optical and thermal images in many sensing and surveillance scenarios as the complementary nature of both modalities can be exploited and the individual drawbacks largely compensated (e.g. [27,3,9,13,7]). …”

Section: Introductionmentioning

confidence: 99%

Exemplar-Based Colour Constancy

Joze

Drew

2012

Procedings of the British Machine Vision Conference 2012

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We address the problem of scene depth recovery within cross-spectral stereo imagery (each image sensed over a differing spectral range). We compare several robust matching techniques which are able to capture local similarities between the structure of crossspectral images and a range of stereo optimisation techniques for the computation of valid depth estimates in this case. Specifically we deal with the recovery of dense depth information from thermal (far infrared spectrum) and optical (visible spectrum) image pairs where large differences in the characteristics of image pairs make this task significantly more challenging than the common stereo case. We show that the use of dense gradient features, based on Histograms of Oriented Gradient (HOG) descriptors, for pixel matching in combination with a strong match optimisation approach can produce largely valid, yet coarse, dense depth estimates suitable for object localisation or environment navigation. The proposed solution is compared and shown to work favourably against prior approaches based on using Mutual Information (MI) or Local Self-Similarity (LSS) descriptors.

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Section: Introductionmentioning

confidence: 99%

Exemplar-Based Colour Constancy

Joze

Drew

2012

Procedings of the British Machine Vision Conference 2012

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“…One potential approach to detect humans is to endow robots of specific sensors such as RFID or thermal sensors (Correa et al, 2012). In spite of high performances, this solution requires ad hoc hardware, usually not available in common robotics platform, limiting the range of possible scenarios.…”

Section: Related Workmentioning

confidence: 99%

Detecting Biological Motion for Human–Robot Interaction: A Link between Perception and Action

et al. 2017

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One of the fundamental skills supporting safe and comfortable interaction between humans is their capability to understand intuitively each other's actions and intentions. At the basis of this ability is a special-purpose visual processing that human brain has developed to comprehend human motion. Among the first "building blocks" enabling the bootstrapping of such visual processing is the ability to detect movements performed by biological agents in the scene, a skill mastered by human babies in the first days of their life. In this paper, we present a computational model based on the assumption that such visual ability must be based on local low-level visual motion features, which are independent of shape, such as the configuration of the body and perspective. Moreover, we implement it on the humanoid robot iCub, embedding it into a software architecture that leverages the regularities of biological motion also to control robot attention and oculomotor behaviors. In essence, we put forth a model in which the regularities of biological motion link perception and action enabling a robotic agent to follow a human-inspired sensory-motor behavior. We posit that this choice facilitates mutual understanding and goal prediction during collaboration, increasing the pleasantness and safety of the interaction.

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“…After comparing several methods, they concluded that the best-performing method for HRI applications, in terms of recognition rate and real-time operation, is LBP-histograms using histogram intersection or Euclidean distance as similarity measures in the visual and thermal spectra. Based on similar ideas, another work [37] proposed the robust detection of humans through thermal and visual information sources that are integrated to detect human-candidate objects, which are further processed to verify the presence of humans and their identity using face information in the thermal and visual spectra. Face detection is used to verify the presence of humans, and face recognition is used to identify them.…”

Section: Person Recognition and Trackingmentioning

confidence: 99%

RoboCup@Home: Analysis and results of evolving competitions for domestic and service robots

Iocchi

Holz

Ruiz‐del‐Solar

et al. 2015

Artificial Intelligence

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Please cite this article in press as: L. Iocchi et al., ROBOCUP@HOME: Analysis and results of evolving competitions for domestic and service robots, Artificial Intelligence (2015), http://dx. AbstractScientific competitions are becoming more common in many research areas of artificial intelligence and robotics, since they provide a shared testbed for comparing different solutions and enable the exchange of research results. Moreover, they are interesting for general audiences and industries. Currently, many major research areas in artificial intelligence and robotics are organizing multiple-year competitions that are typically associated with scientific conferences.One important aspect of such competitions is that they are organized for many years. This introduces a temporal evolution that is interesting to analyze. However, the problem of evaluating a competition over many years remains unaddressed. We believe that this issue is critical to properly fuel changes over the years and measure the results of these decisions. Therefore, this article focuses on the analysis and the results of evolving competitions.In this article, we present the RoboCup@Home competition, which is the largest worldwide competition for domestic service robots, and evaluate its progress over the past seven years. We show how the definition of a proper scoring system allows for desired functionalities to be related to tasks and how the resulting analysis fuels subsequent changes to achieve general and robust solutions implemented by the teams. Our results show not only the steadily increasing complexity of the tasks that RoboCup@Home robots can solve but also the increased performance for all of the functionalities addressed in the competition.We believe that the methodology used in RoboCup@Home for evaluating competition advances and for stimulating changes can be applied and extended to other robotic competitions as well as to multi-year research projects involving Artificial Intelligence and Robotics.

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Human Detection and Identification by Robots Using Thermal and Visual Information in Domestic Environments

Cited by 51 publications

References 35 publications

Exemplar-Based Colour Constancy

Exemplar-Based Colour Constancy

Detecting Biological Motion for Human–Robot Interaction: A Link between Perception and Action

RoboCup@Home: Analysis and results of evolving competitions for domestic and service robots

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