Study on optimal camera arrangement for positioning people in intelligent space

Lee, J.H.; Akiyama, Takanori; Hashimoto, Hideki

doi:10.1109/irds.2002.1041392

Cited by 13 publications

(8 citation statements)

References 7 publications

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“…The study of the stereo positioning accuracy is poorly described in the literature. Most of the articles describe positioning of static objects, for example, [30]. When positioning an object, errors inevitably occur.…”

Section: Extraction Of the Spatial Coordinates From Video Signalmentioning

confidence: 99%

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Observing and Forecasting the Trajectory of the Thrown Body with use of Genetic Programming

Mironov¹,

Gayanov²,

Kurennov³

2019

Adv. sci. technol. eng. syst. j.

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Robotic catching of thrown objects is one of the common robotic tasks, which is explored in a number of papers. This task includes subtask of tracking and forecasting the trajectory of the thrown object. Here we propose an algorithm for estimating future trajectory based on video signal from two cameras. Most of existing implementations use deterministic trajectory prediction and several are based on machine learning. We propose a combined forecasting algorithm where the deterministic motion model for each trajectory is generated via the genetic programming algorithm. Object trajectory is extracted from video sequence by the image processing algorithm, which include Canny edge detection, Random Sample Consensus circle recognition and stereo triangulation. After that rajectory is forecasted using proposed method. Numerical experiments with real trajectories of the thrown tennis ball show that the algorithm is able to forecast the trajectory accurately.

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Section: Extraction Of the Spatial Coordinates From Video Signalmentioning

confidence: 99%

“…When positioning an object, errors inevitably occur. According to the classification proposed by Lee [30], they are divided into three types:…”

Section: Extraction Of the Spatial Coordinates From Video Signalmentioning

confidence: 99%

Observing and Forecasting the Trajectory of the Thrown Body with use of Genetic Programming

Mironov¹,

Gayanov²,

Kurennov³

2019

Adv. sci. technol. eng. syst. j.

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“…Effective service provision requires high-quality input data and appropriate arrangement of the input and output devices. For this reason, many researchers of intelligent environments have studied the optimal arrangement of devices [3], [4]. However, rearranging the devices with each change of spatial environment is arduous and tiresome task.…”

Section: Introductionmentioning

confidence: 99%

The deadlock free path generation algorithm for multi-MoMo in R+iSpace

Park

Nunogaki

Lee

2014

2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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Intelligent environments are the extensive environmental systems that provide information and services to user via robots, displays and speaker. Interaction is realized by networks of sensors installed in the wall and ceilings of buildings. The intelligent environment R+iSpace rearranges devices in physical space, achieving consistent high performance of the environmental system. In the R+iSpace system, devices are mounted on mobile modules (MoMos), which are spatially arranged to suit a required situation. The MoMo path generation algorithm, which was proposed in previous works, did not consider the deadlock situation. Here, we propose a reactive path generation algorithm, in which MoMos sequentially generate their paths based on the positions of other MoMos. The new algorithm is implemented in six layers. Each layer determines the cost of moving to adjacent nodes based on specified criteria, and the next node device node is decided by integrating the results of all layers. The performance of new algorithm is validated in computer simulations.

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“…Accurate detection can be achieved using a video system if privacy is not a concern. For example, Lee and Hashimoto proposed a concept "Intelligent Space" for measuring human action in a room [3,4]. The multi vision system is mainly used for measuring.…”

Section: Introductionmentioning

confidence: 99%

Structural environmental informatization using sensor network with heterogeneous sensors

Tanikawa

Ohara

Ohba

2009

Intel Serv Robotics

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In the present paper, a configuration of a sensor network system for monitoring the usage patterns of a house is proposed. The sensor network system has many active type radio-frequency identifications (RFIDs) as a network node. The RFID has advantages of low cost and low power consumption. Also the RFID can connect various sensors for measuring environment information, since having I/O port as external interface. Environment information is stored on a database through the RFID's wireless radio communication function. The sensor types in this system are variety from slow changing information like temperature and humidity data to event notification like a human detection data. The paper will be described a acquisition procedure for various characteristic sensor data on the same sensor network. Also, the installation locations of the sensors are critical for highly accurate detection of the environmental conditions. Finally, based on the sensor data, capability of analysis of the usage pattern for a house will be discussed.

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Study on optimal camera arrangement for positioning people in intelligent space

Cited by 13 publications

References 7 publications

Observing and Forecasting the Trajectory of the Thrown Body with use of Genetic Programming

Observing and Forecasting the Trajectory of the Thrown Body with use of Genetic Programming

The deadlock free path generation algorithm for multi-MoMo in R+iSpace

Structural environmental informatization using sensor network with heterogeneous sensors

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Study on optimal camera arrangement for positioning people in intelligent space

Cited by 13 publications

References 7 publications

Observing and Forecasting the Trajectory of the Thrown Body with use of Genetic Programming

Observing and Forecasting the Trajectory of the Thrown Body with use of Genetic Programming

The deadlock free path generation algorithm for multi-MoMo in R&#x002B;iSpace

Structural environmental informatization using sensor network with heterogeneous sensors

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Product

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The deadlock free path generation algorithm for multi-MoMo in R+iSpace