Determining operational measures from multi-camera surveillance systems using soft biometrics

CCTV and surveillance networks are increasingly being used for operational as well as security tasks. One emerging area of technology that lends itself to operational analytics is soft biometrics. Soft biometrics can be used to describe a person and detect them throughout a sparse multi-camera network. This enables them to be used to perform tasks such as determining the time taken to get from point to point, and the paths taken through an environment by detecting and matching people across disjoint views. However, in a busy environment where there are 100's if not 1000's of people such as an airport, attempting to monitor everyone is highly unrealistic. In this paper we propose an average soft biometric, that can be used to identity people who look distinct, and are thus suitable for monitoring through a large, sparse camera network. We demonstrate how an average soft biometric can be used to identify unique people to calculate operational measures such as the time taken to travel from point to point.

Activity modelling in crowded environments : a soft decision approach

Probabilistic topic models have recently been used for activity analysis in video processing, due to their strong capacity to model both local activities and interactions in crowded scenes. In those applications, a video sequence is divided into a collection of uniform non-overlaping video clips, and the high dimensional continuous inputs are quantized into a bag of discrete visual words. The hard division of video clips, and hard assignment of visual words leads to problems when an activity is split over multiple clips, or the most appropriate visual word for quantization is unclear. In this paper, we propose a novel algorithm, which makes use of a soft histogram technique to compensate for the loss of information in the quantization process; and a soft cut technique in the temporal domain to overcome problems caused by separating an activity into two video clips. In the detection process, we also apply a soft decision strategy to detect unusual events.We show that the proposed soft decision approach outperforms its hard decision counterpart in both local and global activity modelling.

Noninvasive in vivo assessment of soft contact lens type on tear film surface quality

To evaluate the effect of soft contact lens type on the in vivo tear film surface quality (TFSQ) on daily disposable lenses and to establish whether two recently developed techniques for noninvasive measurement of TFSQ can distinguish between different contact lens types.

Tear film surface quality with rigid and soft contact lenses

Objectives: To measure tear film surface quality (TFSQ) using dynamic high-speed videokeratoscopy during short-term (8 hours) use of rigid and soft contact lenses. Methods: A group of fourteen subjects wore 3 different types of contact lenses on 3 different non-consecutive days (order randomized) in one eye only. Subjects were screened to exclude those with dry eye. The lenses included a PMMA hard, an RGP (Boston XO) and a soft silicone hydrogel lens. Three 30 second long high speed videokeratoscopy recordings were taken with contact lenses in-situ, in the morning and again after 8 hours of contact lens wear, both in normal and suppressed blinking conditions. Recordings were also made on a baseline day with no contact lens wear. Results: The presence of a contact lens in the eye had a significant effect on the mean TFSQ in both natural and suppressed blinking conditions (p=0.001 and p=0.01 respectively, repeated measures ANOVA). TFSQ was worse with all the lenses compared to no lens in the eye (in the afternoon during both normal and suppressed blinking conditions (all p<0.05). In natural blinking conditions, the mean TFSQ for the PMMA and RGP lenses was significantly worse than the baseline day (no lens) for both morning and afternoon measures (p<0.05). Conclusions: This study shows that both rigid and soft contact lenses adversely affect the TFSQ in both natural and suppressed blinking conditions. No significant differences were found between the lens types and materials. Keywords: Tear film surface quality, rigid contact lens, soft contact lens, dynamic high-speed videokeratoscopy

Identifying customer behaviour and dwell time using soft biometrics

In a commercial environment, it is advantageous to know how long it takes customers to move between different regions, how long they spend in each region, and where they are likely to go as they move from one location to another. Presently, these measures can only be determined manually, or through the use of hardware tags (i.e. RFID). Soft biometrics are characteristics that can be used to describe, but not uniquely identify an individual. They include traits such as height, weight, gender, hair, skin and clothing colour. Unlike traditional biometrics, soft biometrics can be acquired by surveillance cameras at range without any user cooperation. While these traits cannot provide robust authentication, they can be used to provide identification at long range, and aid in object tracking and detection in disjoint camera networks. In this chapter we propose using colour, height and luggage soft biometrics to determine operational statistics relating to how people move through a space. A novel average soft biometric is used to locate people who look distinct, and these people are then detected at various locations within a disjoint camera network to gradually obtain operational statistics