Fast and inexpensive color image segmentation for interactive robots

By James Bruce, Tucker R. Balch, Manuela M. Veloso. IEEE/RJS International Conference on Intelligent RObots and Systems, 2000

592 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/f7bc5b8c23e91a426cd6ed37314ac123b6a69667

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In Computer Vision and Pattern Recognition

In Water Science and Technology

Citations in the corpus

Introduction to Autonomous Mobile Robots (2004, unknown): “In this spirit, the CMVision color-tracking software represents a state-of-the-art software solution for color tracking in dynamic environments [47].”
Enabling effective human-robot interaction using perspective-taking in robots (2005, methodology): “The perception specialist uses color segmentation [54] and laser range finding to identify and localize objects, and also receives verbal input.”
Pinatubo: A processing-in-memory architecture for bulk bitwise operations in emerging non-volatile memories (2016, background): “Bitwise operations are very important and widely used by database [26], graph processing [5], bio-informatics [21], and image processing [6].”
Merging chrominance and luminance in early, medium, and late fusion using Convolutional Neural Networks (2015, background): “, 2005], facial region location [Chai and Ngan, 1998], and fast image segmentation for interactive robots [Bruce et al., 2000].”
Yale-CMU-Berkeley dataset for robotic manipulation research (2017, methodology): “The scanner is calibrated using CMVision (Bruce et al., 2000) for pattern detection and Ceres-Solver Table 1.”
Sensing and Manipulating Built-for-Human Environments (2004, unknown): “Color histograms are commonly used to detect pixels of interest,(37,34) and color is often used to detect regions to which a robot should orient.(38) Cardea’s door detection model uses 2D color histograms that represent the probability that a pixel with hue h and saturation s is generated by the sur”
MCMC-based particle filtering for tracking a variable number of interacting targets (2005, methodology): “• Targets were detected using a noisy, but fast, color detector to locate ant-colored regions in an image in the proximity of the nest entrance [7].”
Budburst and leaf area expansion measured with a novel mobile camera system and simple color thresholding (2009, unknown): “However, the transformationofthecolorspaceintothehue,saturation,andluminance (HSL) color space, a simple to implement function, allows for better color constancy with the changing light conditions that may have occurred during image capture (Liu and Moore, 1990; Bruce et al., 2000 ).”
Detection and Localization of Multiple Objects (2006, background): “Oftentimes, these approaches are also highly sensitive to lighting conditions [6].”