object recognition

There was no difference between the two groups in object recognition.

This article assumes that you are familiar with Rational Functional Tester and with the concepts of test automation and object recognition.

Edges in image is important for object recognition and computer analysis, and a large number of edge extraction algorithms are available.

Image-based object recognition is one of computer vision's core challenges, with human faces being perhaps the most compelling scenario.

Moreover, the precision of object recognition can be improved effectively by the combination of SIFT features and normalized DLT algorithm.

Firstly, this paper gives a full summarization of the state-of-art research and development in object recognition and relevant fields.

Its Point &Find interface uses object-recognition technology to help mobile users find services in their area.

The recognition of airplane is one of the applications of object recognition.

Thus continuous transformation learning is an important principle that may contribute to view invariant object recognition.

Perception: Visual Scene Analysis, Object Recognition, Auditory Scene Analysis, Depth Perception, Stereo Vision, Stereograms.

A color-based object recognition and segmentation method is proposed, and is combined with the dilation method to improve the results.

Object recognition and tracking is an important research sub-field in computer vision, which has attracted great concerns of researchers.

Dimensionality reduction is an important preprocessing step before object recognition.

SIFT has proved to be the most robust local invariant feature descriptor in object recognition and matching.

Results show that the method can effectively amend the image quality and improve the dependability of the object recognition.

The research of the binocular vision include camera calibration, ima-ge processing, stereo matching, object recognition, etc.

an object recognition algorithm which integrates the background subtraction algorithm and the temporal differencing algorithm is introduced.

An ultra-wideband quadrature demodulation receiver signal acquisition system for the purpose of object recognition is designed.

Object recognition in cluttered real-world scenes requires local image features that are unaffected by nearby clutter or partial occlusion.

Its mainly research topics include moving object detection, moving object recognition and tracking, abnormal behavior detection and alarm.

The navigation-based object recognition method is quite lightweight and efficient.

As object's motion is a major feature for many videos' content, object recognition is an important process in video retrieval.

Getting exact human position under occlusion is a key problem to object recognition across multiple cameras with overlapped views.

And last, scene understanding and object recognition strongly constrain the selection of attended locations.

It also plays an important role in image restoration, feature extraction, as well as object recognition.

Detection of echo signal is an important part of underwater object recognition.

Visual object recognition is a very active topic in computer vision and pattern recognition area.

A realtime dynamic object recognition and localization method is presented for mobile robot using binocular vision.

Ambient illumination variation across cameras is a challenge for object recognition.

3D object recognition across multiple views is an important problem in the flied of computer vision and pattern recognition.

A new method for moving object recognition and tracking in the intelligent traffic monitoring system was proposed.

In this paper, a new geometric hashing method fitting for the 3D object recognition under perspective transformation is proposed.

High resolution fresco oriented object recognition is separated into two aspects.

Firstly, the candidate evaluation objects are extracted according to the evaluation object recognition.

Axial ratio in- coding shape information of space object is useful for space object recognition.

The three-dimensional object recognition is an important topic in computer vision research.

The viewpoint has been the focus of the debates in many recent object recognition studies.

Mounted on the glasses is a tiny camera, display screen and object recognition system.

Script recording will be generic, in that object recognition will be as ATL or HTML objects, not as Siebel objects.

The ObjectFactory class addresses this issue with dynamic object recognition methods.

The object recognition rule based on the cosine value between original image vector and reconstructed image vector is proposed.

The matching computation for 3D shape of superquadric models is one key problem in 3D object recognition with superquadrics.

Therefore, we cannot use Robot's object-recognition method, since there are no objects inside the terminal window.

Object recognition based on shape is an embranchment of X-ray detection techniques.

This allows for more flexibility in object recognition.

Aiming at these problems, this paper presents a new method for object recognition based on affine statistical invariants.

Finally, this paper proposes an extension of LDA, affine invariant topic model(AITM), and applies AITM to object recognition.

Our method will widen the application foreground of 3D object recognition.

A new affine invariants based on affine geometry for object recognition and matching is proposed in the paper.

A 3D points cloud object recognition algorithm was proposed based on local descriptor.

A 2D object recognition algorithm based on geometry invariant and BP Network. is proposed.

Because of these merits, image fusion is widely used in these areas such as machine vision, digital camera and object recognition and so on.

Finally, the paper set up an object recognition theoretical model that is based on human visual attention mechanism.

It is presented that one hierarchical method based on invariant feature for object recognition and location in complex background.

Founding of Object Recognition Learning Paradigm in KM Mice and Its Application in Detecting Memory Impaired Properties of Compounds

Comparative study of boundary feature description methods for object recognition

Brain Mechanisms of Object Recognition - Neurophysiological Studies

Parameter Estimation for Optimal Object Recognition OptimalParamEstimate

Moment Invariant Stability and Its Features for Object Recognition

Object Recognition- Based Lighting Assistant Landing System for Marine Helicopters

Multi-object recognition using power spectrum optimized joint transform correlator

Automatic Rule Acquisition for Self-Adapting Object Recognition in Engineering Drawings

Scene Perception and Contextual Influences on Individual Object Recognition

Three-dimensional Object Recognition with Rotation-invariant by Structure Light

Translation, Rotation and Scale-Invariant Object Recognition

Application Research on Perceptual Grouping in Object Recognition

Optimal linear representations of images for object recognition OptimalLinearRep

Characteristics of Human Object Recognition Psychophysics Based on Psychophysical Experiments

Application of Projective Invariants in Object Recognition

Object Recognition Using Intensity Properties

An Adaptive Threshold for Color Image Segmentation and Object Recognition

The summarizations on the different brain mechanism study between face recognition and object recognition

Approach to Dynamic Object Recognition with Grid Unit Integers and Region Average

An Algorithm for Object Segmentation and Object Recognition on Outdoor Scene

An Overview of Object Recognition Research at MIT Project Presentations

Combining Interest Points and Edges for Building and Object Recognition

Effects of MCMV-inoculation via the placenta on object recognition ability in fetal mice

Moving Object Recognition in Complex Environment

The Technology of Information Merging in Object Recognition

The Using of Image Processing Technique in Special Object Recognition

A Real-time Object Recognition System Based on Regions Segmentation

Omni-Vision and Front Vision Based Object Recognition for Soccer Robots

Navigation path-based object recognition

Application of Fuzzy Theory and BP Networks in Object Recognition

Design and Implementation of Simulation Software for Space Object Recognition Based on Radar Observing

Object recognition technique in binary image

The Viewpoint Debates in Object Recognition

Three-dimensional object recognition with rotation-invariant based on Moire fringe

One algorithm of radar object recognition based on fuzzy inference and defuzzification

Object Recognition Based on Affine Invariants in Implicit Polynomial Curves

A Fast Object Recognition and Detection Algorithm Based on Gray Difference of Row Scanning

Tips for better test object recognition

A New Method of Object Recognition Using a Neural Network

Natural shape object recognition based on multitemplate subspace and support vector machine

Multi-Object Recognition Model of Vessels Formation Based on Ant Algorithm

Video Monitoring System Based on Moving Object Recognition

Object Recognition of Mechanical Tools Based on Neural Networks

Object Recognition by SVM Based on Wavelet Feature Extraction

Moving Object Recognition Based on Multi-feature Fusion

A New Algorithm of Object Recognition Based on Spectral Library for TM Images

An algorithm of object recognition of ship noise based on SVD

The Research of Object Recognition Based on Multi-Agent Frame System MAFS