Results 11 - 20 of 143

First results on facial feature segmentation and recognition using graph homomorphisms

by Roberto Cesar, Isabelle Bloch - In VI Simpsio IberoAmericano de Reconhecimento de Padres Florianaplis , 2001
"... Abstract. A new method for segmenting facial feature regions (e.g. eyebrows, iris, lips, nostrils,...), in images and video sequences based on graph homomorphisms is introduced in this paper. Firstly, we apply a recently proposed technique based on Gabor Wavelet Networks (GWN) to obtain an approxima ..."
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Abstract. A new method for segmenting facial feature regions (e.g. eyebrows, iris, lips, nostrils,...), in images and video sequences based on graph homomorphisms is introduced in this paper. Firstly, we apply a recently proposed technique based on Gabor Wavelet Networks (GWN) to obtain

Towards Robust Place Recognition for Robot Localization

by Muhammad Muneeb, Ullah Andrzej Pronobis, Barbara Caputo, Jie Luo, Patric Jensfelt, Henrik I. Christensen, M. M. Ullah, A. Pronobis, B. Caputo, J. Luo, P. Jensfelt, H. I. Christensen , 2010
"... Abstract — Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place recognition algorithm should be robu ..."
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of visual recognition algorithms for these tasks, this paper presents a new database, acquired in three different labs across Europe. It contains image sequences of several rooms under dynamic changes, acquired at the same time with a perspective and omnidirectional camera, mounted on a socket. We assess

Inexact Graph Matching for Facial Feature Segmentation and Recognition in Video Sequences: Results on Face Tracking

by Ana Beatriz, V. Graciano, Roberto M. Cesar, Isabelle Bloch
"... Abstract. This paper presents a method for the segmentation and recognition of facial features and face tracking in digital video sequences based on inexact graph matching. It extends a previous approach proposed for static images to video sequences by incorporating the temporal aspect that is inher ..."
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Abstract. This paper presents a method for the segmentation and recognition of facial features and face tracking in digital video sequences based on inexact graph matching. It extends a previous approach proposed for static images to video sequences by incorporating the temporal aspect

Facial Expression Recognition in Image Sequences Using Geometric Deformation Features and Support Vector Machines

by unknown authors
"... Abstract—In this paper, two novel methods for facial expression recognition in facial image sequences are presented. The user has to manually place some of Candide grid nodes to face landmarks depicted at the first frame of the image sequence under examination. The grid-tracking and deformation syst ..."
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Abstract—In this paper, two novel methods for facial expression recognition in facial image sequences are presented. The user has to manually place some of Candide grid nodes to face landmarks depicted at the first frame of the image sequence under examination. The grid-tracking and deformation

Robot Navigation Using Image Sequences

by Christopher Rasmussen, Gregory D. Hager - In Proc. AAAI , 1996
"... We describe a framework for robot navigation that exploits the continuity of image sequences. Tracked visual features both guide the robot and provide predictive information about subsequent features to track. Our hypothesis is that image-based techniques will allow accurate motion without a precise ..."
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We describe a framework for robot navigation that exploits the continuity of image sequences. Tracked visual features both guide the robot and provide predictive information about subsequent features to track. Our hypothesis is that image-based techniques will allow accurate motion without a

ROBUST PLACE RECOGNITION WITHIN MULTI-SENSOR VIEW SEQUENCES USING BERNOULLI MIXTURE MODELS

by Filipe Ferreira, Vitor Santos Jorge Dias
"... Abstract: This article reports on the use of Hidden Markov Models to improve the results of Localization within a sequence of Sensor Views. Local image features (SIFT) and multiple types of features from a 2D laser range scan are all converted into binary form and integrated into a single, binary, F ..."
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Abstract: This article reports on the use of Hidden Markov Models to improve the results of Localization within a sequence of Sensor Views. Local image features (SIFT) and multiple types of features from a 2D laser range scan are all converted into binary form and integrated into a single, binary

Hand Gesture Recognition Based on Combined Features Extraction

by Mahmoud Elmezain, Ayoub Al-hamadi, Bernd Michaelis
"... Abstract—Hand gesture is an active area of research in the vision community, mainly for the purpose of sign language recognition and Human Computer Interaction. In this paper, we propose a system to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
Abstract—Hand gesture is an active area of research in the vision community, mainly for the purpose of sign language recognition and Human Computer Interaction. In this paper, we propose a system to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences

Object Recognition Speech Recognition Scene

by unknown authors
"... • In our work, we apply deep learning in design engineering (specifically, microfluidic device or lab-on-a-chip design). • Controlling shape and location of a fluid stream enables creation of structured materials, preparing biological samples, and engineering heat and mass transport. • Recent work i ..."
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pertinent features from the input images and simultaneously predicts the index of each pillars in the sequence which produces the desired shape (Fig 5).

Cellular Neural Networks For Complex Object Recognition

by Mariofanna Milanova, Ulrich Büker, Heinz Nixdorf , 1998
"... In this paper, the application of CNN associative memories for 3D object recognition is presented. The main idea is to analyse the optical flow in an image sequence of an object. Several features of the optical flow between two succeeding images are calculated and merged to a time series of features ..."
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In this paper, the application of CNN associative memories for 3D object recognition is presented. The main idea is to analyse the optical flow in an image sequence of an object. Several features of the optical flow between two succeeding images are calculated and merged to a time series

Statistical Gabor Graph Based Techniques for the Detection, Recognition, Classification, and Visualization of Human Faces

by Manuel Günther , 2011
"... In this work, I focus in a simple parameter-free statistical model that requires few training data and can be trained fast. I show that the model is well suited for face detection, person identification, and classification of facial properties. For face detection, the well known elastic bunch graph ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
matching algo-rithm is adapted to learn appearance probabilities of facial features. Fur-thermore, texture features are transformed to be used for the detection of faces in different sizes and in-plane rotation angles. In order to place facial landmarks more reliably and to increase face recognition
Results 11 - 20 of 143