Multi-colour switching of polymer stabilized chiral nematic liquid crystal devices

We have fabricated a series of polymer stabilized chiral nematic test cells for use as flexoelectro-optic devices. The devices fabricated were based on commercial chiral nematic mixtures which were polymer stabilized so as to enhance the uniformity and stability of the uniform lying helix texture in the cells. During fabrication and test procedures a series of unusual scattering states have been observed within the devices at different viewing angles. The observations made so far indicate that the properties of the scattering state lies somewhere between the focal conic texture and the Grandjean or planar texture and that the devices exhibit both a helical pitch selective reflection and scattering effect. What is even more dramatic is that the wavelength selectivity of the scattering effect can be tuned by an applied field. In addition, we show that it is possible to achieve good uniform lying helix textures from such devices. Moreover, we show that in certain cases the spontaneous alignment of the helix in the plane of the device opens up the possibility of a new mode of switching. Flexoelectric, Redshift, Coloured scattering, Liquid crystal, Polymer-stabilized liquid-crystal;.

Efficient block segmentation algorithm for true motion estimation

A block-based motion estimation technique is proposed which permits a less general segmentation performed using an efficient deterministic algorithm. Applied to image pairs from the Flower Garden and Table Tennis sequences, the algorithm successfully localizes motion discontinuities and detects uncovered regions. The algorithm is implemented in C on a Sun Sparcstation 20. The gradient-based motion estimation required 28.8 s CPU time, and 500 iterations of the segmentation algorithm required 32.6 s.

Segmentation and recognition using structure from motion point clouds

We propose an algorithm for semantic segmentation based on 3D point clouds derived from ego-motion. We motivate five simple cues designed to model specific patterns of motion and 3D world structure that vary with object category. We introduce features that project the 3D cues back to the 2D image plane while modeling spatial layout and context. A randomized decision forest combines many such features to achieve a coherent 2D segmentation and recognize the object categories present. Our main contribution is to show how semantic segmentation is possible based solely on motion-derived 3D world structure. Our method works well on sparse, noisy point clouds, and unlike existing approaches, does not need appearance-based descriptors. Experiments were performed on a challenging new video database containing sequences filmed from a moving car in daylight and at dusk. The results confirm that indeed, accurate segmentation and recognition are possible using only motion and 3D world structure. Further, we show that the motion-derived information complements an existing state-of-the-art appearance-based method, improving both qualitative and quantitative performance. © 2008 Springer Berlin Heidelberg.

Semi-supervised video segmentation using tree structured graphical models

We present a novel, implementation friendly and occlusion aware semi-supervised video segmentation algorithm using tree structured graphical models, which delivers pixel labels alongwith their uncertainty estimates. Our motivation to employ supervision is to tackle a task-specific segmentation problem where the semantic objects are pre-defined by the user. The video model we propose for this problem is based on a tree structured approximation of a patch based undirected mixture model, which includes a novel time-series and a soft label Random Forest classifier participating in a feedback mechanism. We demonstrate the efficacy of our model in cutting out foreground objects and multi-class segmentation problems in lengthy and complex road scene sequences. Our results have wide applicability, including harvesting labelled video data for training discriminative models, shape/pose/articulation learning and large scale statistical analysis to develop priors for video segmentation. © 2011 IEEE.

Automatic object segmentation from calibrated images

This paper addresses the problem of automatically obtaining the object/background segmentation of a rigid 3D object observed in a set of images that have been calibrated for camera pose and intrinsics. Such segmentations can be used to obtain a shape representation of a potentially texture-less object by computing a visual hull. We propose an automatic approach where the object to be segmented is identified by the pose of the cameras instead of user input such as 2D bounding rectangles or brush-strokes. The key behind our method is a pairwise MRF framework that combines (a) foreground/background appearance models, (b) epipolar constraints and (c) weak stereo correspondence into a single segmentation cost function that can be efficiently solved by Graph-cuts. The segmentation thus obtained is further improved using silhouette coherency and then used to update the foreground/background appearance models which are fed into the next Graph-cut computation. These two steps are iterated until segmentation convergences. Our method can automatically provide a 3D surface representation even in texture-less scenes where MVS methods might fail. Furthermore, it confers improved performance in images where the object is not readily separable from the background in colour space, an area that previous segmentation approaches have found challenging. © 2011 IEEE.

Initializing Vision Based Trackers Using Semantic Texton Forests

Vision based tracking can provide the spatial location of project related entities such as equipment, workers, and materials in a large-scale congested construction site. It tracks entities in a video stream by inferring their motion. To initiate the process, it is required to determine the pixel areas of the entities to be tracked in the following consecutive video frames. For the purpose of fully automating the process, this paper presents an automated way of initializing trackers using Semantic Texton Forests (STFs) method. STFs method performs simultaneously the segmentation of the image and the classification of the segments based on the low-level semantic information and the context information. In this paper, STFs method is tested in the case of wheel loaders recognition. In the experiments, wheel loaders are further divided into several parts such as wheels and body parts to help learn the context information. The results show 79% accuracy of recognizing the pixel areas of the wheel loader. These results signify that STFs method has the potential to automate the initialization process of vision based tracking.

UV durable colour pigment doped SmA liquid crystal composites for outdoor trans-reflective bi-stable displays

High brightness trans-reflective bi-stable displays based on smectic A (SmA) liquid crystals (LCs) can have nearly perfect transparency in the clear state and very high reflection in the scattered state. Because the LC material in use is stable under UV radiation, this kind of displays can stand for strong day-light and therefore be ideal for outdoor applications from e-books to public signage and advertisement. However, the colour application has been limited because the traditional colourants in use are conventional dyes which are lack of UV stability and that their colours are easily photo bleached. Here we present a colour SmA display demonstrator using pigments as colourant. Mixing pigments with SmA LCs and maintain the desirable optical switching performance is not straightforward. We show here how it can be done, including how to obtain fine sized pigment nano-particles, the effects of particle size and size distribution on the display performance. Our optimized pigments/SmA compositions can be driven by a low frequency waveform (∼101Hz) to a scattered state to exhibit colour while by a high frequency waveform (∼103Hz) to a cleared state showing no colour. Finally, we will present its excellent UV life-time (at least >7.2 years) in comparison with that of dye composition (∼2.4 years). The complex interaction of pigment nano-particles with LC molecules and the resulting effects on the LC electro-optical performances are still to be fully understood. We hope this work will not only demonstrate a new and practical approach for outdoor reflective colour displays but also provide a new material system for fundamental liquid crystal colloid research work. © 2012 SPIE.

Video segmentation with superpixels

Due to its importance, video segmentation has regained interest recently. However, there is no common agreement about the necessary ingredients for best performance. This work contributes a thorough analysis of various within- and between-frame affinities suitable for video segmentation. Our results show that a frame-based superpixel segmentation combined with a few motion and appearance-based affinities are sufficient to obtain good video segmentation performance. A second contribution of the paper is the extension of [1] to include motion-cues, which makes the algorithm globally aware of motion, thus improving its performance for video sequences. Finally, we contribute an extension of an established image segmentation benchmark [1] to videos, allowing coarse-to-fine video segmentations and multiple human annotations. Our results are tested on BMDS [2], and compared to existing methods. © 2013 Springer-Verlag.