Pawan Sinha

Pedestrian detection using wavelet templates

This paper presents a trainable object detection architecture that is applied to detecting people in static images of cluttered scenes. This problem poses several challenges. People are highly non-rigid objects with a high degree of variability in size, shape, color, and texture. Unlike previous approaches, this system learns from examples and does not rely on any a priori (hand-crafted) models or on motion. The detection technique is based on the novel idea of the wavelet template that defines the shape of an object in terms of a subset of the wavelet coefficients of the image. It is invariant to changes in color and texture and can be used to robustly define a rich and complex class of objects such as people. We show how the invariant properties and computational efficiency of the wavelet template make it an effective tool for object detection.

Face Recognition by Humans: Nineteen Results All Computer Vision Researchers Should Know About

A key goal of computer vision researchers is to create automated face recognition systems that can equal, and eventually surpass, human performance. To this end, it is imperative that computational researchers know of the key findings from experimental studies of face recognition by humans. These findings provide insights into the nature of cues that the human visual system relies upon for achieving its impressive performance and serve as the building blocks for efforts to artificially emulate these abilities. In this paper, we present what we believe are 19 basic results, with implications for the design of computational systems. Each result is described briefly and appropriate pointers are provided to permit an in-depth study of any particular result

Functional neuroanatomy of biological motion perception in humans

We used whole brain functional MRI to investigate the neural network specifically engaged in the recognition of “biological motion” defined by point-lights attached to the major joints and head of a human walker. To examine the specificity of brain regions responsive to biological motion, brain activations obtained during a “walker vs. non-walker” discrimination task were compared with those elicited by two other tasks: (i) non-rigid motion (NRM), involving the discrimination of overall motion direction in the same “point-lights” display, and (ii) face-gender discrimination, involving the discrimination of gender in briefly presented photographs of men and women. Brain activity specific to “biological motion” recognition arose in the lateral cerebellum and in a region in the lateral occipital cortex presumably corresponding to the area KO previously shown to be particularly sensitive to kinetic contours. Additional areas significantly activated during the biological motion recognition task involved both, dorsal and ventral extrastriate cortical regions. In the ventral regions both face-gender discrimination and biological motion recognition elicited activation in the lingual and fusiform gyri and in the Brodmann areas 22 and 38 in superior temporal sulcus (STS). Along the dorsal pathway, both biological motion recognition and non-rigid direction discrimination gave rise to strong responses in several known motion sensitive areas. These included Brodmann areas 19/37, the inferior (Brodmann Area 39), and superior parietal lobule (Brodmann Area 7). Thus, we conjecture that, whereas face (and form) stimuli activate primarily the ventral system and motion stimuli primarily the dorsal system, recognition of biological motion stimuli may activate both systems as well as their confluence in STS. This hypothesis is consistent with our findings in stroke patients, with unilateral brain lesions involving at least one of these areas, who, although correctly reporting the direction of the point-light walker, fail on the biological motion task.

Effects of early experience on children's recognition of facial displays of emotion.

The present research examines visual perception of emotion in both typical and atypical development. To examine the processes by which perceptual mechanisms become attuned to the contingencies of affective signals in the environment, the authors measured the sequential, content-based properties of feature detection in emotion recognition processes. To evaluate the role of experience, they compared typically developing children with physically abused children, who were presumed to have experienced high levels of threat and hostility. As predicted, physically abused children accurately identified facial displays of anger on the basis of less sensory input than did controls, which suggests that physically abused children have facilitated access to representations of anger. The findings are discussed in terms of experiential processes in perceptual learning.

The role of eyebrows in face recognition

A fundamental challenge in face recognition lies in determining which facial characteristics are important in the identification of faces. Several studies have indicated the significance of certain facial features in this regard, particularly internal ones such as the eyes and mouth. Surprisingly, however, one rather prominent facial feature has received little attention in this domain: the eyebrows. Past work has examined the role of eyebrows in emotional expression and nonverbal communication, as well as in facial aesthetics and sexual dimorphism. However, it has not been made clear whether the eyebrows play an important role in the identification of faces. Here, we report experimental results which suggest that for face recognition the eyebrows may be at least as influential as the eyes. Specifically, we find that the absence of eyebrows in familiar faces leads to a very large and significant disruption in recognition performance. In fact, a significantly greater decrement in face recognition is observed in the absence of eyebrows than in the absence of eyes. These results may have important implications for our understanding of the mechanisms of face recognition in humans as well as for the development of artificial face-recognition systems.

Statistical context priming for object detection

There is general consensus that context can be a rich source of information about an objects identity, location and scale. However the issue of how to formalize centextual influences is still largely open. Here we introduce a simple probabilistic framework for modeling the relationship between context and object properties. We represent global context information in terms of the spatial layout of spectral components. The resulting scheme serves as an effective procedure for context driven focus of attention and scale-selection on real-world scenes. Based on a simple holistic analysis of an image, the scheme is able to accurately predict object locations and sizes.

Contribution of Color to Face Recognition

One of the key challenges in face perception lies in determining how different facial attributes contribute to judgments of identity. In this study, we focus on the role of color cues. Although color appears to be a salient attribute of faces, past research has suggested that it confers little recognition advantage for identifying people. Here we report experimental results suggesting that color cues do play a role in face recognition and their contribution becomes evident when shape cues are degraded. Under such conditions, recognition performance with color images is significantly better than that with gray-scale images. Our experimental results also indicate that the contribution of color may lie not so much in providing diagnostic cues to identity as in aiding low-level image-analysis processes such as segmentation.

Autism as a disorder of prediction

Significance Autism is characterized by diverse behavioral traits. Guided by theoretical considerations and empirical data, this paper develops the hypothesis that many of autisms salient traits may be manifestations of an underlying impairment in predictive abilities. This impairment renders an otherwise orderly world to be experienced as a capriciously “magical” one. The hypothesis elucidates the information-processing roots of autism and, thereby, can aid the identification of neural structures likely to be differentially affected. Behavioral and neural measures of prediction might serve as early assays of predictive abilities in infants, and serve as useful tools in intervention design and in monitoring their effectiveness. The hypothesis also points to avenues for further research to determine molecular and circuit-level causal underpinnings of predictive impairments. A rich collection of empirical findings accumulated over the past three decades attests to the diversity of traits that constitute the autism phenotypes. It is unclear whether subsets of these traits share any underlying causality. This lack of a cohesive conceptualization of the disorder has complicated the search for broadly effective therapies, diagnostic markers, and neural/genetic correlates. In this paper, we describe how theoretical considerations and a review of empirical data lead to the hypothesis that some salient aspects of the autism phenotype may be manifestations of an underlying impairment in predictive abilities. With compromised prediction skills, an individual with autism inhabits a seemingly “magical” world wherein events occur unexpectedly and without cause. Immersion in such a capricious environment can prove overwhelming and compromise one’s ability to effectively interact with it. If validated, this hypothesis has the potential of providing unifying insights into multiple aspects of autism, with attendant benefits for improving diagnosis and therapy.

Is Pigmentation Important for Face Recognition? Evidence from Contrast Negation

It is extraordinarily difficult to recognize a face in an image with negated contrast, as in a photographic negative. The variation among faces can be partitioned into two general sources: (a) shape and (b) surface reflectance, here termed ‘pigmentation’. To determine whether negation differentially affects the processing of shape or pigmentation, we made two sets of faces where the individual faces differed only in shape in one set and only in pigmentation in the other. Surprisingly, matching performance was significantly impaired by contrast negation only when the faces varied in pigmentation. This provides evidence that the perception of pigmentation, not shape, is selectively disrupted by negation and, by extension, that pigmentation contributes to the neural representation of face identity.

Perceiving Illumination Inconsistencies in Scenes

The human visual system is adept at detecting and encoding statistical regularities in its spatiotemporal environment. Here, we report an unexpected failure of this ability in the context of perceiving inconsistencies in illumination distributions across a scene. Prior work with arrays of objects all having uniform reflectance has shown that one inconsistently illuminated target can ‘pop out’ among a field of consistently illuminated objects (eg Enns and Rensink, 1990 Science 247 721–723; Sun and Perona, 1997 Perception 26 519–529). In these studies, the luminance pattern of the odd target could be interpreted as arising from either an inconsistent illumination or inconsistent pigmentation of the target. Either cue might explain the rapid detection. In contrast, we find that once the geometrical regularity of the previous displays is removed, the visual system is remarkably insensitive to illumination inconsistencies, both in experimental stimuli and in altered images of real scenes. Whether the target is interpreted as oddly illuminated or oddly pigmented, it is very difficult to find if the only cue is deviation from the regularity of illumination or reflectance. Our results allow us to draw inferences about how the visual system encodes illumination distributions across scenes. Specifically, they suggest that the visual system does not verify the global consistency of locally derived estimates of illumination direction.