Object Detection and Matching with Mobile Cameras Collaborating with Fixed Cameras
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Feature detection and description constitute important steps of many computer vision applications such as object detection and panorama stitching. Since those steps are computationally heavy, they might occupy significant portion of the full operation. Alt ...
The sliding window approach is the most widely used technique to detect objects from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the sc ...
In many 3-D object-detection and pose-estimation problems, run-time performance is of critical importance. However, there usually is time to train the system. We introduce an approach that takes advantage of this fact by formulating wide-baseline matching ...
Springer2013
, , ,
We have developed a method for the detection of both generic flight neighbouring aircrafts and those on a collision course. Our approach employs a sliding window linear Support Vector Machine (SVM) classifier with a Histogram of Oriented Gradients (HOG) fe ...
Feature description for local image patch is widely used in computer vision. While the conventional way to design local descriptor is based on expert experience and knowledge, learning based methods for designing local descriptor become more and more popul ...
Institute of Electrical and Electronics Engineers2014
The sliding window approach is the most widely used technique to detect an object from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the ...
Academic Press Inc Elsevier Science2013
,
This paper presents a method for the automated detection of dropped objects in surveillance scenarios, which is a very important task for abandoned object detection. Our method works in single views and exploits prior information of the scene, such as geom ...
The sliding window approach is the most widely used technique to detect objects from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the sc ...
We introduce a learning-based approach to detect repeatable keypoints under drastic imaging changes of weather and lighting conditions to which state-of-the-art keypoint detectors are surprisingly sensitive. We first identify good keypoint candidates in mu ...
Detecting interest points is a key component of vision-based estimation algorithms, such as visual odometry or visual SLAM. Classically, interest point detection has been done with methods such as Harris, FAST, or DoG. Recently, better detectors have been ...
