A Fusion Framework for Camouflaged Moving Foreground Detection in the Wavelet Domain

Detecting camouflaged moving foreground objects has been known to be difficult due to the similarity between the foreground objects and the background. Conventional methods cannot distinguish the foreground from background due to the small differences between them and thus suffer from under-detection of the camouflaged foreground objects. In this paper, we present a fusion framework to address this problem in the wavelet domain. We first show that the small differences in the image domain can be highlighted in certain wavelet bands. Then the likelihood of each wavelet coefficient being foreground is estimated by formulating foreground and background models for each wavelet band. The proposed framework effectively aggregates the likelihoods from different wavelet bands based on the characteristics of the wavelet transform. Experimental results demonstrated that the proposed method significantly outperformed existing methods in detecting camouflaged foreground objects. Specifically, the average F-measure for the proposed algorithm was 0.87, compared to 0.71 to 0.8 for the other state-of-the-art methods.Comment: 13 pages, accepted by IEEE TI

Recognition by directed attention to recursively partitioned images

A learning/recognition model (and instantiating program) is described which recursively combines the learning paradigms of conceptual clustering (Michalski, 1980) and learning-from-examples to resolve the ambiguities of real-world recognition. The model is based on neuropsychological and psychological evidence that the visual system is analytic, hierarchical, and composed of a parallel/serial dichotomy (many, see conclusions by Crick, 1984). Emulating the experimental evidence, parallel processes in the model decompose the image into components and cluster the constituents in much the same way as the image processing technique known as moment analysis (Alt, 1962). Serial, attentive mechanisms then reassemble the decompositions by investigating spatial relationships between components. The use of attentive mechanisms extends the moment analysis technique to handle alterations in structure and solves the contention problem created by combining the two learning paradigms. The contention results from a disagreement between the teacher and the model on what constitutes the salient features at the highest level of the symbol. There are four cases ZBT must handle, two of which result from the disagreement with the teacher. The parallel/serial dichotomy represents a vertical/horizontal tradeoff between the invariant and variant features of a domain. The resultant learned hierarchy allows ZBT to recognize structural differences while avoiding problems of exponential growth

No compromise between metabolism and behavior of decorator crabs in reduced pH conditions.

Many marine calcifiers experience metabolic costs when exposed to experimental ocean acidification conditions, potentially limiting the energy available to support regulatory processes and behaviors. Decorator crabs expend energy on decoration camouflage and may face acute trade-offs under environmental stress. We hypothesized that under reduced pH conditions, decorator crabs will be energy limited and allocate energy towards growth and calcification at the expense of decoration behavior. Decorator crabs, Pelia tumida, were exposed to ambient (8.01) and reduced (7.74) pH conditions for five weeks. Half of the animals in each treatment were given sponge to decorate with. Animals were analyzed for changes in body mass, exoskeleton mineral content (Ca and Mg), organic content (a proxy for metabolism), and decoration behavior (sponge mass and percent cover). Overall, decorator crabs showed no signs of energy limitation under reduced pH conditions. Exoskeleton mineral content, body mass, and organic content of crabs remained the same across pH and decoration treatments, with no effect of reduced pH on decoration behavior. Despite being a relatively inactive, osmoconforming species, Pelia tumida is able to maintain multiple regulatory processes and behavior when exposed to environmental pH stress, which underscores the complexity of responses within Crustacea to ocean acidification conditions

Disrupted Dwelling: Forensic Aesthetics and the Visibility of Violence

The aim of the present text is to offer an interpretation of Eyal Weizman’s_concept of forensic aesthetics, demonstrating how this approach reveals the ways in which the aesthetic perception of violence, trauma, and decomposition of human dwelling can be transformed in the current digital optical war regime. Forensic aesthetics tries to grasp a_forensic sensibility as both an aesthetic and political practice, requiring individuals to become sensitive to violence and be able to comprehend and experience the affects of disintegration, trauma, and despair that are characteristic of the experience of the survivor. The environment, dwelling, and architecture are not only inert observers, but rather have become material witnesses of crimes, violence, and destruction of various dwellings inhabited by various species. The application of digital technologies in forensic aesthetics carries a strong ethical appeal to avoid injustice. Traces and fragments of evidence, as well as multiple videos and images, are synchronized and recomposed within digital architectural environments and dwellings, as an optical and interpretative tool that shapes a new type of aesthetics

Infrared thermochromic antenna composite for self-adaptive thermoregulation

Self-adaptive thermoregulation, the mechanism living organisms use to balance their temperature, holds great promise for decarbonizing cooling and heating processes. The functionality can be effectively emulated by engineering the thermal emissivity of materials to adapt to background temperature variations. Yet, solutions that marry large emissivity switching (${\Delta}\epsilon$) with scalability, cost-effectiveness and design freedom are still lacking. Here, we fill this gap by introducing infrared dipole antennas made of tunable thermochromic materials. We demonstrate that non-spherical antennas (rods, stars and flakes) made of vanadium-dioxide can exhibit a massive (~200-fold) increase in their absorption cross-section as temperature rises. Embedding these antennas in polymer films, or simply spraying them directly, creates free-form thermoregulation composites, featuring an outstanding ${\Delta}\epsilon\sim0.6$ in spectral ranges that can be tuned at will. Our research paves the way for versatile self-adaptive heat management solutions (coatings, fibers, membranes and films) that could find application in radiative-cooling, heat-sensing, thermal-camouflage, and other

Physical Adversarial Attack meets Computer Vision: A Decade Survey

Although Deep Neural Networks (DNNs) have achieved impressive results in computer vision, their exposed vulnerability to adversarial attacks remains a serious concern. A series of works has shown that by adding elaborate perturbations to images, DNNs could have catastrophic degradation in performance metrics. And this phenomenon does not only exist in the digital space but also in the physical space. Therefore, estimating the security of these DNNs-based systems is critical for safely deploying them in the real world, especially for security-critical applications, e.g., autonomous cars, video surveillance, and medical diagnosis. In this paper, we focus on physical adversarial attacks and provide a comprehensive survey of over 150 existing papers. We first clarify the concept of the physical adversarial attack and analyze its characteristics. Then, we define the adversarial medium, essential to perform attacks in the physical world. Next, we present the physical adversarial attack methods in task order: classification, detection, and re-identification, and introduce their performance in solving the trilemma: effectiveness, stealthiness, and robustness. In the end, we discuss the current challenges and potential future directions.Comment: 32 pages. Under Revie