Trainable Visual Models for Object Class Recognition

نویسنده

  • Andrew Zisserman
چکیده

Recognizing object classes, such as cars, planes or elephants, in an image or a video remains one of the most challenging problems in Computer Vision. However, recently a number of successes have been achieved by using ideas and algorithms from statistical learning theory, where visual models are trained using positive and negative examples of the class.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models

The remarkable abilities of the primate visual system have inspired the construction of computational models of some visual neurons. We propose a trainable hierarchical object recognition model, which we call S-COSFIRE (S stands for Shape and COSFIRE stands for Combination Of Shifted FIlter REsponses) and use it to localize and recognize objects of interests embedded in complex scenes. It is in...

متن کامل

شناسایی نوع و مدل وسیله نقلیه با استفاده از مجموعه بخش‌های متمایز‌کننده

In fine-grained recognition, the main category of object is well known and the goal is to determine the subcategory or fine-grained category. Vehicle make and model recognition (VMMR) is a fine-grained classification problem. It includes several challenges like the large number of classes, substantial inner-class and small inter-class distance. VMMR can be utilized when license plate numbers ca...

متن کامل

Parallel Spatial Pyramid Match Kernel Algorithm for Object Recognition using a Cluster of Computers

This paper parallelizes the spatial pyramid match kernel (SPK) implementation. SPK is one of the most usable kernel methods, along with support vector machine classifier, with high accuracy in object recognition. MATLAB parallel computing toolbox has been used to parallelize SPK. In this implementation, MATLAB Message Passing Interface (MPI) functions and features included in the toolbox help u...

متن کامل

Vision and Pattern Recognition , Puerto Rico , June 1997 Pedestrian Detection Using Wavelet

This paper presents a trainable object detection architecture that is applied to detecting people in static images of cluttered scenes. This problem poses several challenges. People are highly non-rigid objects with a high degree of variability in size, shape, color, and texture. Unlike previous approaches, this system learns from examples and does not rely on any a priori (hand-crafted) models...

متن کامل

Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition

In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class membership (and not object location or configuration). This method learns both a model of local part appearance and a model of the spatial relations between those parts. In contrast, other work using such a weakly supervised learning...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004