Collecting the Dead (10 page)

Most people think they’re opposites or at least that they’re quite different from one another. They’re not. They’re actually the same thing, only separated by time. When I started walking up those steps, had I had a little foresight I could have run, but by the time I pause in front of Diane’s office, it’s too late.

In hindsight I realize I
should
have run.

See what I mean? It’s all in the timing.

Rising from her desk, Diane says, “Good morning, Steps,” in the warmest of voices; she’s devious that way. “Did you get some breakfast?”

I hold up a half-eaten granola bar in one hand and a Diet Pepsi in the other.

“Oh,” she says pointedly. “That’s healthy.”

“
This
,” I say, thrusting out the granola bar, “is healthy. This”—I wave the soda bottle—“is caffeine. I didn’t sleep well. We didn’t land till sometime after midnight.”

“Twelve thirty-seven
A.M.
, I saw.” Then she drops the hammer. “Since you’re here, let me introduce you to Miss Heather Jennings … but … wait … I believe you two already know each other, don’t you?”

Evil.

Devious.

Heather swivels in her seat and gives me a generous smile.

She smells good, like coconut and citrus; all tropical-island-like. Suddenly the hangar is stuffy and hot, and my cheeks are flush with warm blood as my palms begin to sweat. She’s beautiful, smart, sweet; impossible to hate. Damn her.

“So,” Diane says, turning back to Heather, “I’ve made reservations at the Hearthfire Grill for six o’clock, if that works?”

The Hearthfire? That was our restaurant.

“That’s perfect,” Heather says, rising from her chair and hitching her bag up onto her shoulder.

“Do you need a ride?” Diane asks.

“No, I drove my Honda up.”

“The convertible?”

Heather nods, a grin on her face.

“I just love that car,” Diane trills. She’s practically pawing Heather’s arm; it’s disgusting. “Do you remember how to get there?”

“Sure, I can find it. I’ve got my GPS. Besides, Steps took me there a half dozen times.” Turning, she eyes me from top to bottom, a coy smile on her face, neither approving nor disapproving. “Is it still his favorite restaurant?”

“They know him by name. I’m surprised he doesn’t have a reserved parking spot.”

“I go there
maybe
three times a month,” I say in protest, but then realize I’m really not part of this conversation.

“Thanks, Diane,” Heather purrs.

“My pleasure, hon.”

Then, just like that, she’s down the stairs, across the hangar, and out the door, taking the coconut trees, oranges, limes, and the tropical breeze with her.

“Nice to see you two are still so chummy,” I say, wiping my brow and pouring on the sarcasm in my very best how-could-you? voice. “Dinner at the Hearthfire Grill? That’s nice. Special.”

“It is, isn’t it?” Diane replies, her eyes all a-twinkle.

*   *   *

The surveillance video from Bellis Fair Mall is sitting on my desk when I flip on the light: a single disk in a white paper sleeve. I expected more, but a note attached to the disk indicates that mall security reviewed five days of video and copied only those segments where there was a car parked in the spot I indicated. “Thank yooou, buddy,” I say softly as I slide the DVD into the computer. Instead of spending hours scanning through irrelevant video, my search has been reduced to seven short clips.

The first video shows a mother and her daughter in an eighties-style station wagon with wood-grain siding. Wagons, vans, SUVs, and the like are always good vehicle choices for killers, but I know from previous video that Leonardo is a dark-haired male, average in every way.

Clip two is what appears to be a teenage boy in a beat-up red and white Bronco, and this is followed by a family in a motor home, a man in a black sedan, another man in a burgundy sedan who parks for a while and then leaves without ever stepping foot out of the car, two women in a Subaru with bikes on the roof, and lastly, a white fifteen-passenger van loaded down with boys on some kind of outing. The top of the van bristles with canoes and pixelated lumps that might be suitcases; more gear is strapped to the back.

I watch each clip carefully, dutifully, before going back to number four—the man in the black sedan. I watch him exit the vehicle and point his arm at the hood; the lights flash briefly as the car locks. Starting at the driver’s door, he walks around the front of the car, down the passenger side, and back to the driver’s door, where he checks the door handle.

Hello, Leonardo
.

There’s no doubt it’s him. Each time I’ve seen his shine at the mall he does the same thing before leaving his car: he walks in a slow, methodical circle around the entire vehicle.

Is it a ritual? Some type of protection circle? Is he checking the car; the tires? Or is he just obsessive-compulsive, driven by his own mind to go through strict, repetitive routines before doing anything? Jimmy and I have discussed it a dozen times, but we’re still not any closer to an answer. As for me, I’m betting on the obsessive-compulsive disorder … with a little bit of psycho wack-job thrown in.

The car is too far away to make out the plate. That’s the joke when it comes to security cameras; in almost every case they’re either too far away or too cheaply built to show any real detail. Casinos and banks invest in better-quality equipment and generally have better placement, but they’re the exception to the rule.

After transferring the video to my thumb drive, I swap disks and start working on Alison Lister’s kidnapper. The video is bad and I’m not optimistic we’ll be able to identify the make, let alone the model. The truck is just too far away, the resolution is too poor, and the only view is from the side. A portion of the front and rear can be seen at an angle, but few details are revealed. Regardless, I transfer the video.

Plucking the thumb drive from the USB slot, I pause just long enough to check my voice mail: two messages, Mom reminding me about the family picnic in July and my optometrist telling me I’m overdue for an exam.

“I’m heading to the S.O.,” I tell Diane as I pause in her doorway. “I need to see if Dex can ID Leonardo’s car, plus I have the video from Redding.”

“It’s the sheriff’s office, not the S.O.,” Diane replies without looking up. “Just because we work for the government doesn’t mean we have to assign acronyms to everything.”

“S.O.,” I whisper. “S.O.”

An eight-by-ten color photo sits on top of a manila folder at the edge of Diane’s desk. I recognize it immediately. I should; I took it two years ago at Washoe Lake. Picking it up, I stare at the pattern fashioned from rocks in the high desert soil. “I see Jimmy already talked to you.”

Diane nods. “I should have a list for you later this afternoon.”

I place the photo back on her desk, on top of the manila folder. “We have two. I’m betting we find more, making this guy a serial.”

“I hope you’re wrong.”

I tap the photo twice. “He left his calling card; what kind of sick bastard does that? He’s marking his conquests, maybe keeping score.” Diane meets my gaze and I give a curt nod. “He’s a serial; you’ll see.”

*   *   *

Dexter Allen’s office at the Whatcom County Sheriff’s Office is a cluttered hole in the basement of the crumbling county jail. Half-buried in the ground with only a handful of windows that look up at the sidewalk outside, the administrative offices of the sheriff’s office are decrepit and worn. The walls are worn, the structural concrete is worn, the floor tiles are worn—even the air is worn, stagnant from poor circulation.

The texture of the ceiling tiles is mismatched due to their constant replacement as various liquids leak down from the jail above: gray water from the jail shower, soapy water from the jail kitchen, and questionable water from the jail toilets, which are frequently and intentionally stuffed with jail toilet paper to cause an overflow.

These internal rainstorms are frequent enough that the shelves in the archives room down the hall are carefully and constantly covered in heavy plastic to protect the original case reports. Sometimes the liquid is clear, other times it’s brown. In one case, brown chunks spilled out onto a desk in the Detectives Division, prompting several detectives to collect the sample for analysis, convinced that the inmates were now defecating on them by proxy.

Dex pays little mind to the crumbling edifice.

Surrounded by his monitors, he crunches data, reviews case reports, and sips Diet Pepsi. The only decoration in the bland office consists of several Civil War paintings on the wall and his diplomas from the Defense Language Institute in Monterey, California, and the Naval War College in Newport, Rhode Island. He laughingly calls himself a relic of the Cold War, but after seventeen years as a Russian linguist, then intelligence analyst, and finally as a project manager for various “operations” at the Office of Naval Intelligence, he somehow landed this unlikely position as a crime analyst with the sheriff’s office.

He’s on the phone when I walk into his office and plop down in a chair. I only half-listen to the call, something about a wanted burglary suspect hiding out in a house near Maple Falls. No doubt he’s talking to one of the deputies, maybe a detective, but certainly someone keen on getting their hands on the suspect.

The call ends and Dex shoots me a grin.

“Diane said you’d be stopping by. So … how’s Heather?”

“Oh, shut up.”

He chuckles; I’m glad my misery provides joy for so many people. Handing him the thumb drive, I say, “I need a little FVA.”

Forensic vehicle analysis, or FVA, is an analytical process developed by Dex over years and made real in the form of a photo database. The idea came to him after too many blurry surveillance images crossed his desk: an armed robbery showing only the vehicle’s taillights, a rape where the only clue was the image of the front corner of a truck as it pulled into a parking space just off-camera, a homicide with only nighttime images of a passing SUV.

Faced with this onslaught of consistently bad imagery, he did what every good analyst does: He changed the game. Dex doesn’t think outside the box, he redefines it.

When I first heard about FVA two years ago, I called him an out-of-the-box thinker, meaning it as a compliment. He smiled and shook his head. “There is no box.” When I gave him a questioning look, he said, “The idea of thinking machines was once way outside the box, right? Yet now computers are as mainstream as TV, radio, and the printing press—they’re right in the middle of the box with everything else we take for granted day in and day out; therefore there is no box, just vision and actualization.”

He tapped the side of his head with his index finger: “Computer visualized”—then he tapped the CPU on the floor next to his desk—“computer actualized.”

I remember telling him he sounded like a Zen version of Tony Robbins; he just laughed.

Plugging the thumb drive into the USB port, Dex starts a frame-separation program, then selects the video from Bellis Fair and opens it in the program. “Say when,” he murmurs as he fast-forwards through the video clip.

“Stop!” I say fifteen seconds later as the black vehicle first rolls on-screen. He tags the first frame and then tags another frame after Leonardo parks. With the parameters for the beginning and end of the frame separation identified, Dex clicks a button and starts the extraction. Within seconds the segment of video is dissected into almost six hundred separate still-frame images showing angles of the front, side, and rear.

Dex is already lost in the hunt, almost oblivious to my presence. His hands work the keyboard and the mouse at a furious pace as he views one photo after another, enlarging some, sharpening others. He selects a dozen of the best images, including shots of the front, side, and rear of Leonardo’s car, and then opens the forensic vehicle analysis database.

“See here,” he says, drawing my attention to the rear of the vehicle with his index finger, “the little flash. That’s the third brake light. That’s what I call a ‘window-high’ position because it’s at the inside top edge of the back window. You’ll also notice the license plate is not down on the bumper, but up between the taillights; that’s a ‘center-high’ position. The picture quality is about average for surveillance video—”

“Which means it sucks,” I say.

“Which means it sucks,” he replies. “Still, there’s plenty to crunch through the database.” He moves his finger to a dark spot behind the rear door. “There’s some kind of reflection here, looks like a window behind the door—hard to be certain with the car being black. Let’s take a look from another angle.”

Pulling two side shots and a front angle to the top of the image stack, he immediately taps the screen and with an I-told-you-so tone says, “There it is! See the reflection? There’s definitely a window behind the rear door. That narrows our search considerably.”

“How so?”

“It’s just not that common, particularly with the newer cars. Let’s run it and see what we get.” Pulling up a query screen, he selects each of the identified criteria, then adds two more, pointing out that the taillights are configured in a “horizontal sweep” and have “bleed,” a term he uses to identify taillights that extend into the trunk. After checking boxes next to each criterion, he hits the query button and the database instantly returns thirty results with links to photos for each one.

“Volvos, Audis, Hondas, and Hyundais, but none appear to have what I’m looking for,” Dex hums as he clicks methodically through the pictures. “Oh, wait. Here we go.” Tapping the screen several times, he points at the array of images on display. “That’s it. No doubt whatsoever. It’s a first-generation Saturn L-series sedan, which was manufactured for model years 2000 through 2005 … though it looks like this one is a 2000-through-2002 model.”

“How can you possibly know that?”

“Look at the front. The L-series got a face-lift for 2003 that included a much larger grille and a redesigned front fascia. That,” he adds emphatically, “is the pre-face-lift model.”