Charles Otto

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There has been a growing interest in automatic age estimation from facial images due to a variety of potential applications in law enforcement, security control, and humancomputer interaction. However, despite advances in automatic age estimation, it remains a challenging problem. This is because the face aging process is determined not only by intrinsic(More)
Demographic estimation entails automatic estimation of age, gender and race of a person from his face image, which has many potential applications ranging from forensics to social media. Automatic demographic estimation, particularly age estimation, remains a challenging problem because persons belonging to the same demographic group can be vastly different(More)
As face recognition applications progress from constrained sensing and cooperative subjects scenarios (e.g., driver's license and passport photos) to unconstrained scenarios with uncooperative subjects (e.g., video surveillance), new challenges are encountered. These challenges are due to variations in ambient illumination, image resolution, background(More)
There is growing interest in achieving age invariant face recognition due to its wide applications in law enforcement. The challenge lies in that face aging is quite a complicated process, which involves both intrinsic and extrinsic factors. Face aging also influences individual facial components (such as the mouth, eyes, and nose) differently. We propose a(More)
Given the prevalence of social media websites, one challenge facing computer vision researchers is to devise methods to search for persons of interest among the billions of shared photos on these websites. Despite significant progress in face recognition, searching a large collection of unconstrained face images remains a difficult problem. To address this(More)
Given a large collection of unlabeled face images, we address the problem of clustering faces into an unknown number of identities. This problem is of interest in social media, law enforcement, and other applications, where the number of faces can be of the order of hundreds of million, while the number of identities (clusters) can range from a few thousand(More)
In this paper, we present a real-time automatic vision-based rail inspection system, which performs inspections at 16 km/h with a frame rate of 20 fps. The system robustly detects important rail components such as ties, tie plates, and anchors, with high accuracy and efficiency. To achieve this goal, we first develop a set of image and video analytics and(More)
Many modern retail stores have self-checkout stations where customers can ring up their own orders without the assistance of any store personnel. To promote customer honesty these systems often weigh each item as it is placed in the bag to confirm that it has the expected mass for the product scanned. In our system we augment this basic check with an(More)
For safety purposes, railroad tracks need to be inspected on a regular basis for physical defects or design noncompliances. Such track defects and non-compliances, if not detected in a timely manner, may eventually lead to grave consequences such as train derailments. In this paper, we present a real-time automatic vision-based rail inspection system, with(More)