Boosting colored local features for generic object recognition
نویسندگان
چکیده
منابع مشابه
Colored Local Invariant Features for Object Description
This paper addresses the problem of combining color and geometric invariants for object description by proposing a novel colored invariant local feature descriptor. The proposed approach uses scale-space theory to detect the most geometrically robust features in a physical-based color invariant space. The stability and the distinction of the detected features are compared with the SIFT approach...
متن کاملGeneric Object Recognition with Strangeness and Boosting
People can quickly recognize enormous number of rigid/non-rigid object, such as cars, faces, trees, regardless of the viewpoint, lighting, illumination and local deformation. How to recognize generic object has been a hard problem for long time in psychophysics, neurobiology and computation. Based on the research of psychophysics and neurobiology, human interprets the image scene (label class) ...
متن کاملWeak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique. This allows the use of very diverse sets of visual features in the learning process within a common framework: Boosting — together with a weak hypotheses finder — may choose very inhomogeneous features as most relev...
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 کاملImage representation for generic object recognition using higher-order local autocorrelation features on posterior probability images
This paper presents a novel image representation method for generic object recognition by using higher-order local autocorrelations on posterior probability images. The proposed method is an extension of the bag-of-features approach to posterior probability images. The standard bag-of-features approach is approximately thought of as a method that classifies an image to a category whose sum of p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Pattern Recognition and Image Analysis
سال: 2008
ISSN: 1054-6618,1555-6212
DOI: 10.1134/s1054661808020193