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This paper proposes an object movement detection method covering large areas of a room by using multiple cameras. When object movement detection for whole of a room is performed, there are several challenging difficulties: sizes of objects on the camera images are small, non-objects such as humans also exist on the images, objects are sometimes difficult to detect in specific viewpoints because of...
A microwave Doppler sensor can monitor human motion without contact. It can sense wide range of motion from minute oscillation like respiration to large movement like walking because it measures the distance change between the target and the sensor as signal phase change. However, the proper method for the signal phase estimation is different between motion and respiration measurement. In this paper,...
Laser based environment recognition technologies have been developed recently. Especially moving objects detection and classification by laser scanners mounted on a mobility is required for mobile robots and autonomous cars. In this paper, we propose a moving objects detection and classification method based on grid trajectories acquired from sequential laser scan data. Grid trajectories are obtained...
Vision based human articulated body pose tracking has been historically important. Because analyzing multiple human activities, especially interaction between human in cluttered scenes is essential in visual surveillance scenarios, multiple people tracking has enjoyed much attention in human robot interaction research in recent years. In this paper, we newly introduce a robust framework for multiple...
Laser based tracking systems have been developed for mobile robotics and intelligent surveillance areas. Existing systems estimate only human positions. In this paper, we propose a method for human pose estimation represented by human head and waist position using only laser range finders. Two features of human cross-sectional contours are extracted from laser scanner data scanning on the height of...
Human interaction based on conversation and gestures is very important to realize the natural communication. This paper proposes a conversation system composed of topic selection module, conversation control module and utterance selection module. First, we apply a Bayesian network for the topic selection, and Boltzmann selection for the control of conversation. We apply term frequency inverse document...
In this paper, we propose a novel robust action recognition framework with the following capabilities: 1) online encoding motions to multi-label sequence where the output in each frame is a tuple of labels rather than a single label, 2) providing efficient automatic relevant motion selection framework, 3) learning systems so as to be optimal for online multi-label sequence classification. As for multi-label...
In this paper, we present a novel framework to recover human body pose on multi camera systems. Our framework leverages 3D voxel data, which are reconstructed from multi-camera systems. The use of voxel data leads to viewpoint-free estimation, which benefits in that reconstruction of a training model is needless in different multi-camera arrangements. Other notable aspects of our approach are real-time...
In this paper, a novel approach is proposed to recover human body pose from 3D voxel data. The use of voxel data leads to viewpoint-free estimation, which benefits in that reconstruction of a training model is needless in different multi-camera arrangements. Other notable aspects of our approach are real-time ensuring speed (up to 30[FPS]), flexibility towards various complex motions, and robustness...
In this paper, we propose wrapped boosting that is extension of boosting algorithm for robust online action recognition. Boosting algorithm is one of ensemble learning algorithm and is also known as a feature selector. In our previous work utilizing boosting, we achieved automatic feature selection and robust model-based action classifiers which had very small calculation cost based on posture information...
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