HCI increasingly engages with the concept of time, with many studies focusing on how temporal relations are produced and reconfigured through computing technologies. However, less attention is paid to the impact of temporality on researchers themselves and specifically their capacity for ethical reflection and action. This paper explores the interplay between temporal features and ethical reflection in HCI research projects. Through a reflective multi-ethnography of nine research projects, we examine how temporal features can influence ethical capacity across the lifecycle of research. The study employs infrastructural and chronopolitical analysis (after Star and Sharma) and offers a range of considerations for researchers to help activate greater temporal awareness for everyday wisdom, to acknowledge temporal power, mobilise responsibility, counter isolation in interdisciplinarity, and promote collective action and dynamic methodologies for temporal research. The study responds to calls for more ethnographic approaches to temporality that address specific HCI needs and focus on practice.

25th ACM Interaction Design and Children 25th Conference (IDC 2026). June 22nd – 25th 2026, Brighton UK

We propose a simple and useful idea based on cross-ratio constraint for wide-baseline matching and 3D reconstruction. Most existing methods exploit feature points and planes from images. Lines have always been considered notorious for both matching and reconstruction due to the lack of good line descriptors. We propose a method to generate and match new points using virtual lines constructed using pairs of keypoints, which are obtained using standard feature point detectors. We use cross-ratio constraints to obtain an initial set of new point matches, which are subsequently used to obtain line correspondences. We develop a method that works for both calibrated and uncalibrated camera configurations. We show compelling line-matching and large-scale 3D reconstruction.

A scanning window type pedestrian detector is presented that uses both appearance and motion information to find walking people in surveillance video. We extend the work of Viola, Jones and Snow [10] to use many more frames as input to the detector thus allowing a much more detailed analysis of motion. The resulting detector is about an order of magnitude more accurate than the detector of Viola, Jones and Snow. It is also computationally efficient, processing frames at the rate of 5 Hz on a 3 GHz Pentium processor.

This paper describes a pedestrian detection system that integrates image intensity information with motion information. We use a detection style algorithm that scans a detector over two consecutive frames of a video sequence. The detector is trained (using AdaBoost) to take advantage of both motion and appearance information to detect a walking person. Past approaches have built detectors based on appearance information, but ours is the first to combine both sources of information in a single detector. The implementation described runs at about 4 frames/second, detects pedestrians at very small scales (as small as 20/spl times/15 pixels), and has a very low false positive rate. Our approach builds on the detection work of Viola and Jones. Novel contributions of this paper include: i) development of a representation of image motion which is extremely efficient, and ii) implementation of a state of the art pedestrian detection system which operates on low resolution images under difficult conditions (such as rain and snow).

A novel deformable template is presented which detects the boundary of an open hand in a grayscale image. A dynamic programming algorithm enhanced by pruning techniques finds the hand contour in the image in as little as 19 seconds without initialization by the user. The template is translation- and rotation-invariant and accommodates shape deformation, significant occlusion and background clutter, and the presence of multiple hands.

We describe an approach to detecting, locating and normalizing road signs. The approach will apply provided: (i) the signs have stereotypical boundary shapes (i.e. rectangular, or hexagonal-of course, we allow for these shapes to be distorted by projection to unknown viewpoint), (ii) the writing on the sign has one uniform color and the rest of the sign has a second uniform color (we allow for the color of the illuminant to be unknown). We show that the approach works even under significant illuminant color changes, viewpoint direction, shadowing, and occlusion. This work is part of a project intended to help people who are blind, or whose sight is impaired.

Previous work has developed an approach for estimating shape and albedo from multiple images assuming Lambertian reflectance with single light sources. The main contributions of this paper are: (i) to show how the approach can be generalized to include ambient background illumination, (ii) to demonstrate the use of the integrability constraint for solving this problem, and (iii) an iterative algorithm which is able to improve the analysis by finding shadows and rejecting them.