Local features are usually used to describe pedestrian appearance. While most of existing pedestrian detection methods don’t make full use of context cues, such as associated relationships between local different locations. This paper proposes two novel kinds of local associated features, gradient orientation associated feature (GOAF) and local difference of ACF (ACF-LD), to exploit context inf...

This article presents a shape extraction and results of a preliminary validation stage for a pedestrian detection system based on the use of active contours. The complete system is based on the use of both far infrared and visible cameras to detect areas that potentially contain pedestrians; in order to validate and filter such result a refinement of the human shape by means of active contours ...

The idea behind the experiments in section 4.1 of the main paper is to demonstrate that, within a single framework, varying the features can replicate the jump in detection performance over a ten-year span (2004 2014), i.e. the jump in performance between VJ and the current state-of-the-art. See figure 1 for results on INRIA and Caltech-USA of the following methods (all based on SquaresChnFtrs,...

In this paper, we propose to integrate sparse 3D depth information into pedestrian detection task, in order to achieve a fast boost in performance. Our proposed method uses a probabilistic way to integrate image-feature-based detection and sparse depth estimation together. The depth information is used as a cue, and provides additional discriminative ability for the detection. There are two con...

In video surveillance, classification of visual data can be very hard, due to the scarce resolution and the noise characterizing the sensors’ data. In this paper, we propose a novel feature, the ARray of COvariances (ARCO), and a multi-class classification framework operating on Riemannian manifolds. ARCO is composed by a structure of covariance matrices of image features, able to extract infor...

Pedestrian classifiers decide which image windows contain a pedestrian. In practice, such classifiers provide a relatively high response at neighbor windows overlapping a pedestrian, while the responses around potential false positives are expected to be lower. An analogous reasoning applies for image sequences. If there is a pedestrian located within a frame, the same pedestrian is expected to...

Advanced Driver Assistance Systems are used to increase the security of vehicles. Computer Vision is one of the main technologies used for this aim. Lane marks recognition, pedestrian detection, driver drowsiness or road sign detection and recognition are examples of these systems. The last one is the goal of this paper. A system that can detect and recognize road signs based on color and shape...

In 2005, we automated a forklift-based Hot Metal Carrier to be capable of typical metal transfer operations around a smelter. The project was highly successful and the vehicle has demonstrated hundreds of hours of live autonomous operations to thousands of people from industry and the public. As a result of the exposure and success of the project, we have expanded its focus to demonstrate how v...

Paper-by-paper results make it easy to miss the forest for the trees.We analyse the remarkable progress of the last decade by discussing the main ideas explored in the 40+ detectors currently present in the Caltech pedestrian detection benchmark. We observe that there exist three families of approaches, all currently reaching similar detection quality. Based on our analysis, we study the comple...

Real-Time Pedestrian detection and tracking methods are the state-of-the-art techniques in present driver assistance systems. However, pedestrian detection and tracking methods that exploit the parallel processing capabilities of heterogeneous high performance computing devices such as FPGAs (or GPUs) with sensor fusion(camera and Lidar), a technology that potentially will replace ECUs in a com...