We demonstrate a multiscale pedestrian detector operating in near real time (5 fps on 640x480 images) with state-of-the-art detection performance. The computational bottleneck of ...
We present a scalable and incremental approach for creating interactive image-based walkthroughs from a dynamically growing collection of photographs of a scene. Prior approaches,...
This paper presents a new descriptor for human detection in still images. It is referred to as isotropic granularity-tunable gradients partition (IGGP), which is extended from gra...
This paper shows how semantic attribute features can be used to improve object classification performance. The semantic attributes used fall into five groups: scene (e.g. `road...
We introduce a novel skeleton extraction algorithm in binary and gray-scale images, based on the anisotropic heat diffusion analogy. We propose to diffuse image in the dominance o...
In this paper, we propose a method for simultaneous human full-body pose tracking and activity recognition from time-of-flight (ToF) camera images. Simple and sparse depth cues ar...
Loren Arthur Schwarz, Diana Mateus, Victor Castane...
In interest point based human action recognition, local descriptors are used to represent information in the neighbourhood around each extracted space-time interest point. The per...
In this paper we propose a novel approach to introducing semantic relations into the bag-of-words framework. We use the latent semantic models, such as LSA and pLSA, in order to d...
Recognizing 3D objects from arbitrary view points is one of the most fundamental problems in computer vision. A major challenge lies in the transition between the 3D geometry of o...
Many practical applications require an accurate knowledge of the extrinsic calibration (i.e., pose) of a moving camera. The existing SLAM and structure-from-motion solutions are n...