Authors:
Tanwi Mallick
;
Partha Pratim Das
and
Arun Kumar Majumdar
Affiliation:
Indian Institute of Technology, India
Keyword(s):
Image Formation and Preprocessing, Device Characterization and Modelling, Multi-Kinect Models of Image Formation, IR Interference Noise.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Device Calibration, Characterization and Modeling
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Multimodal and Multi-Sensor Models of Image Formation
Abstract:
KinectTM, a low-cost multimedia sensing device, has revolutionized human computer interaction (HCI) by
making various applications of human activity tracking affordable and widely available. Often multiple
Kinects are used in imaging applications to improve the field of view, depth of field and uni-directional vision
of a single Kinect. Unfortunately, multiple Kinects lead to IR Interference Noise (IR Noise, in short) in the
depth map. In this paper we analyse the estimators for interference noise, survey various imaging techniques
to mitigate the interference at source, and characterize them in parallel to a well-known classification system
in telecom industry. Finally we compare their performance from reported literature and outline our on-going
research to control interference noise by software shuttering.