An object detection system finds objects of the real world present either in a digital image or
a video, where the object can belong to any class of objects namely humans, cars, etc. In …

Clustering image pixels is an important image segmentation technique. While a large
amount of clustering algorithms have been published and some of them generate …

Clustering refers to the process of extracting maximally coherent groups from a set of objects
using pairwise, or high-order, similarities. Traditional approaches to this problem are based …

We present a method that can dramatically accelerate object detection with part based
models. The method is based on the observation that the cost of detection is likely …

While there are a large amount of clustering algorithms proposed in the literature, the
clustering results of existing algorithms usually depend on user-specified parameters …

In this paper, we propose an approach for object detection via structural feature selection
and part-based shape model. It automatically learns a shape model from cluttered training …

Abstract Multi-Video Summarization (MVS) aims at condensing a large number of web
videos by the same search query into a compact storyboard or video skimming. Although …

Feature combination is a popular method for improving object classification performances. In
this paper we present a simple and effective weighting scheme for feature combination …

Generally the performance of a vehicle detector will decrease rapidly, when it is trained on a
fixed training set but applied to a specific scene with view changes. The reason is that in the …

In this paper, we propose a novel framework for object detection and recognition in cluttered
images, given a single hand-drawn example as model. Compared with previous work, our …