title: On the use of a low-cost thermal sensor to improve Kinect people detection in a mobile robot.
abstract: Detecting people is a key capability for robots that operate in populated environments. In this paper, we have adopted a hierarchical approach that combines classifiers created using supervised learning in order to identify whether a person is in the view-scope of the robot or not. Our approach makes use of vision, depth and thermal sensors mounted on top of a mobile platform. The set of sensors is set up combining the rich data source offered by a Kinect sensor, which provides vision and depth at low cost, and a thermopile array sensor. Experimental results carried out with a mobile platform in a manufacturing shop floor and in a science museum have shown that the false positive rate achieved using any single cue is drastically reduced. The performance of our algorithm improves other well-known approaches, such as C4 and histogram of oriented gradients (HOG).
authors.affiliation: Autonomous and Smart Systems Unit, IK4-TEKNIKER, Iaki Goenaga 5, Eibar, Spain. loreto.susperregi@tekniker.es.
authors.forename: Loreto
authors.initials: L
authors.lastname: Susperregi
authors.forename: Basilio
authors.initials: B
authors.lastname: Sierra
authors.forename: Modesto
authors.initials: M
authors.lastname: Castrillón
authors.forename: Javier
authors.initials: J
authors.lastname: Lorenzo
authors.forename: Jose María
authors.initials: JM
authors.lastname: Martínez-Otzeta
authors.forename: Elena
authors.initials: E
authors.lastname: Lazkano
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D004784:Environmental Monitoring / Q000295:instrumentation* / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D015203:Reproducibility of Results; D012371:Robotics / Q000295:instrumentation*; D060388:Support Vector Machine; D013817:Thermography / Q000295:instrumentation* / Q000379:methods