Real-time RGB-D based people detection and tracking for mobile robots and head-worn cameras

Jafari, Omid Hosseini; Mitzel, Dennis; Leibe, Bastian

doi:10.1109/icra.2014.6907688

Cited by 151 publications

(127 citation statements)

References 18 publications

Supporting

Mentioning

126

Contrasting

Unclassified

Order By: Relevance

“…Obstacle is detected by laser and from images, traversable area is identified using stored knowledge for humanoid robot. Jafari et al [28] used RGB-D camera for environment perception. In [29] a wearable system is proposed to detect and avoid obstacles based on ultrasonic sensor.…”

Section: Related Workmentioning

confidence: 99%

Obstacle Detection in Indoor Environment for Visually Impaired Using Mobile Camera

Rahman

Ullah

2018

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Abstract. Obstacle detection can improve the mobility as well as the safety of visually impaired people. In this paper, we present a system using mobile camera for visually impaired people. The proposed algorithm works in indoor environment and it uses a very simp le technique of using few p re-stored floor images. In indoor environ ment all unique floor types are considered and a single image is stored for each unique floor type. These floor images are considered as reference images. The algorithm acquires an input image frame and then a region of interest is selected and is scanned for obstacle using pre-stored floor images. The algorithm compares the present frame and the next frame and co mpute mean square error of the two frames. If mean square error is less than a threshold value α then it means that there is no obstacle in the next frame. If mean square error is greater than α then there are t wo possibilit ies; either there is an obstacle or the floor type is changed. In order to check if the floor is changed, the algorithm co mputes mean square error of next frame and all stored floor types. If minimu m of mean square error is less than a threshold value α then flour is changed otherwise there exist an obstacle. The proposed algorithm works in real-time and 96% accuracy has been achieved.

show abstract

Section: Related Workmentioning

confidence: 99%

Obstacle Detection in Indoor Environment for Visually Impaired Using Mobile Camera

Rahman

Ullah

2018

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…They have been used with great success for motion capture [16,17] and are becoming increasingly popular for people detection in robotics applications [13,18,14,10]. However, the former requires the algorithms to be trained on very large training databases, which may not always be easy to create, to achieve the desired level of performance while the latter usually do not make provisions for the fact that people may occlude each other.…”

Section: Introductionmentioning

confidence: 99%

Probability occupancy maps for occluded depth images

Bagautdinov

Fleuret

Fua

2015

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

View full text Add to dashboard Cite

We propose a novel approach to computing the probabilities of presence of multiple and potentially occluding objects in a scene from a single depth map. To this end, we use a generative model that predicts the distribution of depth images that would be produced if the probabilities of presence were known and then to optimize them so that this distribution explains observed evidence as closely as possible.This allows us to exploit very effectively the available evidence and outperform state-of-the-art methods without requiring large amounts of data, or without using the RGB signal that modern RGB-D sensors also provide.

show abstract

“…For close-range, appearance-based people detection and tracking we developed a real-time RGB-D based multi-person tracker (Jafari et al, 2014), which aims at making maximal use of the depth information from the RGB-D sensors to speed up computation. It classifies the observed 3D points into object candidates, ground, and fixed structures, e.g.…”

Section: Tracking Based On Rgb-d Datamentioning

confidence: 99%

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports

Triebel

Arras

Alami

et al. 2016

Springer Tracts in Advanced Robotics

Self Cite

202

124

View full text Add to dashboard Cite

We present an ample description of a socially compliant mobile robotic platform, which is developed in the EU-funded project SPENCER. The purpose of this robot is to assist, inform and guide passengers in large and busy airports. One particular aim is to bring travellers of connecting flights conveniently and efficiently from their arrival gate to the passport control. The uniqueness of the project stems from the strong demand of service robots for this application with a large potential impact for the aviation industry on one side, and on the other side from the scientific advancements in social robotics, brought forward and achieved in SPENCER. The main contributions of SPENCER are novel methods to perceive, learn, and model human social behavior and to use this knowledge to plan appropriate actions in realtime for mobile platforms. In this paper, we describe how the project advances the fields of detection and tracking of individuals and groups, recognition of human social relations and activities, normative human behavior learning, socially-aware task and motion planning, learning socially annotated maps, and conducting empirical experiments to assess socio-psychological effects of normative robot behaviors.

show abstract

Real-time RGB-D based people detection and tracking for mobile robots and head-worn cameras

Cited by 151 publications

References 18 publications

Obstacle Detection in Indoor Environment for Visually Impaired Using Mobile Camera

Obstacle Detection in Indoor Environment for Visually Impaired Using Mobile Camera

Probability occupancy maps for occluded depth images

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports

Contact Info

Product

Resources

About