Statistical Object Recognition Including Color Modeling
نویسندگان
چکیده
In this paper an appearance-based statistical approach for localization and classification of 3-D objects in 2-D color images with real heterogeneous backgrounds is presented. The object feature extraction is done separately for the red, green, and blue channel. We compute six dimensional local feature vectors directly from pixel values in the images using wavelet multiresolution analysis. The first and second component of the feature vectors depend on the pixel values in the red channel, the third and fourth in the green channel, and fifth and sixth in the blue channel. Then we define an object area as a function of 3-D transformations and represent the feature vectors as probability density functions. In the recognition phase we use an algorithm based on maximum likelihood estimation for object localization and classification. Experiments made on a real data set with 39600 images compare the recognition rates for the new algorithm, which uses the color information of objects, with the results in the case of gray level images.
منابع مشابه
Recognition of Objects Represented in Different Color Spaces
In this article we present a statistical framework for automatic classification and localization of 3D objects in 2D images. The new functionality of the framework allows us to use objects represented in different color spaces including gray level, RGB, and Lab formats. First, the objects are preprocessed and described by local wavelet features. Second, statistical modeling of these features un...
متن کاملApplication of Combined Local Object Based Features and Cluster Fusion for the Behaviors Recognition and Detection of Abnormal Behaviors
In this paper, we propose a novel framework for behaviors recognition and detection of certain types of abnormal behaviors, capable of achieving high detection rates on a variety of real-life scenes. The new proposed approach here is a combination of the location based methods and the object based ones. First, a novel approach is formulated to use optical flow and binary motion video as the loc...
متن کاملEfficient Non-Parametric Adaptive Color Modeling Using Fast Gauss Transform
Modeling the color distribution of a homogeneous region is used extensively for object tracking and recognition applications. The color distribution of an object represents a feature that is robust to partial occlusion, scaling and object deformation. A variety of parametric and non-parametric statistical techniques have been used to model color distributions. In this paper we present a non-par...
متن کاملAnalysis of Cluttered Scenes Using an Elastic Matching Approach for Stereo Images
We present a system for the automatic interpretation of cluttered scenes containing multiple partly occluded objects in front of unknown, complex backgrounds. The system is based on an extended elastic graph matching algorithm that allows the explicit modeling of partial occlusions. Our approach extends an earlier system in two ways. First, we use elastic graph matching in stereo image pairs to...
متن کامل