We present an approach that directly uses curvature cues
in a discriminative way to perform object recognition. We
show that integrating curvature information substantially
impr...
Antonio Monroy, Angela Eigenstetter and Björn Omm...
Over the last decade, the availability of public image repositories and recognition benchmarks has enabled rapid progress in visual object category and instance detection. Today we...
Kevin Lai, Liefeng Bo, Xiaofeng Ren and Dieter Fox
Detecting people remains a popular and challenging problem in computer vision. In this paper, we analyze parts-based models for person detection to determine which components of t...
Over the last years, object detection has become a more and more active field of research in robotics. An important problem in object detection is the need for sufficient labeled ...
We propose a new coherent framework for joint object detection, 3D layout estimation, and object supporting region segmentation from a single image. Our approach is based on the m...
This paper discusses the use of Binary Partition Trees (BPTs) for object detection. BPTs are hierarchical region-based representations of images. They define a reduced set of regio...
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...
In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, th...
Evaluation of object detection algorithms is a non-trivial task: a detection result is usually evaluated by comparing the bounding box of the detected object with the bounding box...