Active vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Information Retrieval
Human Activity Recognition Using Multidimensional Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
Efficient adaptive density estimation per image pixel for the task of background subtraction
Pattern Recognition Letters
Bilayer Segmentation of Live Video
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Fusing Time-of-Flight Depth and Color for Real-Time Segmentation and Tracking
Dyn3D '09 Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging
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In this paper authors have presented a method to localize and detect human being from Kinect captured sequence of images. The proposed method takes a sequence of gray (G) scale image and the corresponding depth (D) image as input. The gray scale image and the depth information are captured using two different sensors within the same device, Kinect and the processing are executed in the processor attached with Kinect. The proposed method localizes the human by using their motion along x, y direction and then considers all pixels connected with those pixels and over a 3D plane to accomplish the segmentation with an accuracy of 77%. Experimental results demonstrate that our method is robust against existing method for human localization.